├── Decision Tree Algorithm.py ├── NLP.py ├── Poster Sentiment Analysis by Combining Lexicon-based and Machine Learning Methods - CSC 522 Project-page-001.jpg ├── Poster Sentiment Analysis by Combining Lexicon-based and Machine Learning Methods - CSC 522 Project.pdf ├── README.md ├── bucket.csv ├── dic.csv ├── intense.csv └── tweetylabel.csv /Decision Tree Algorithm.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | Created on Thu Apr 19 12:30:59 2018 4 | 5 | @author: Riddhiman Sherlekar & Harsh Mehta 6 | """ 7 | 8 | 9 | import pandas as pd #importing pandas library to manipulate data frames 10 | import numpy as np # importing numpy library for mathematical calculation 11 | import operator # 12 | data = pd.read_csv("C:\\Users\\rsher\\Desktop\\features_update_2.csv") #reading the data into a data frame 13 | 14 | 15 | class classifier: 16 | def __init__(self, true=None, false=None, column=-1, split=None, result=dict()): 17 | self.true=true #it is used to identify the true decision nodes 18 | self.false=false #it is used to identify the false decision nodes 19 | self.column=column #the column index of criteria that is being tested 20 | self.split=split #it assigns the split point based on entropy 21 | self.result=result #it stores the result in the form of an dictionary 22 | 23 | 24 | 25 | def key_labels(data): #This function is used to return the unique class labels from the data 26 | keys = [] 27 | for i in range(0, len(data)): #For loop is used to store unique class/keys from dataset 28 | if data.iloc[i,len(data.columns)-1] in keys: 29 | continue 30 | else: 31 | keys.append(data.iloc[i,len(data.columns)-1]) 32 | return keys 33 | 34 | keys = key_labels(data) 35 | 36 | def entropy_cal(data, keys): #This function is used to return the entropy of parent node / data and the count of class 37 | count = [0]*len(keys) 38 | ent = [0]*len(keys) 39 | lgth = len(data) 40 | for i in range(0,len(data)): #A for loop is used to calculate the count of each class in a dataset 41 | for j in range(0,len(keys)): 42 | if data.iloc[i,len(data.columns)-1] == keys[j]: 43 | count[j] += 1 44 | for j in range(0,len(keys)): #A for loop is used to calculate the entropy of data 45 | if count[j] != 0: 46 | ent[j] = (count[j]/float(lgth))*np.log2(count[j]/float(lgth)) #Numpy Library is used for calculating the Log2 47 | ent = [-x for x in ent] 48 | entropy = sum(ent) 49 | return entropy, count 50 | 51 | def entropy_data(data, keys): #This fucntion is used to calculate entropy of each attribute at every split point and then store the attribute, best split point and entropy 52 | len_keys = len(keys) 53 | ent_dict = {} 54 | split_dict = {} 55 | #print(data) 56 | if len(data.columns) > 1: #If loop is executed if the number of columns in dataset is greater than 1 57 | 58 | for i in range(0,len(data.columns)-1): #A for loop is executed to carry out entropy calculations for each attribute 59 | if len(data[data.columns[i]].unique()) > 1: #If the number of unique values in an attribute is greater than one, then the if loop is executed 60 | entropy_min = np.log2(len(keys)) # Initially the minimum value of entropy is set as the maximum possible entropy value, i.e. log(n) where n is the number of unique classes 61 | test = data[data.columns[[i,len(data.columns)-1]]] #A dataset is created having the selected attribute and its label values to find the split point 62 | max_value = test.iloc[:,0].max() 63 | min_value = test.iloc[:,0].min() 64 | y = min_value #the initial value of split point is set as the minimum value of the selected attribute 65 | while (y < max_value): #a while loop is executed untill the split point value reaches the maximum value of that attribute 66 | left = [] #an empty list is created to store the labels of the dataset with value <= split point 67 | right = [] #an empty list is created to store the labels of the dataset with value > the split point 68 | for x in range(0, len(test)): #a for loop is created to append the attribute values in the "left" and "right" lists 69 | if test.iloc[x,0] <= y: 70 | left.append(test.iloc[x,1]) 71 | else: 72 | right.append(test.iloc[x,1]) 73 | 74 | 75 | split_pair = [left, right] 76 | ent_pair = [0,0] 77 | for sp_val in range(0,2): #A for loop is created to calculate the entropy of the left split and right split 78 | count = [0]*len_keys 79 | prop = [0]*len_keys 80 | for sp_ct in range(0,len(split_pair[sp_val])): 81 | lgth = len(split_pair[sp_val]) 82 | for j in range(0,len_keys): 83 | if split_pair[sp_val][sp_ct] == keys[j]: 84 | count[j] += 1 85 | for j in range(0, len_keys): 86 | if count[j] != 0: 87 | prop[j] = (count[j]/float(lgth))*np.log2(count[j]/float(lgth)) 88 | ent_pair[sp_val] = sum(prop) 89 | 90 | ent_pair = [-x for x in ent_pair] 91 | entropy = (ent_pair[0]*len(left)/float(len(test))) + (ent_pair[1]*len(right)/float(len(test))) #The resultant entropy of the split is stored in "entropy" 92 | if entropy < entropy_min: #if the entropy of the split is less than the minimum entropy, then the if loop is executed which will overwrite the minimum entropy and best split point 93 | splitvalue = y 94 | entropy_min = entropy 95 | y = y + 1 96 | ent_dict[test.columns[0]] = entropy_min #the minimum entropy of each attribute is appened in the dictionary ent_dict having the attribute as the key 97 | split_dict[test.columns[0]] = splitvalue #attribute is stored as a key and the split point is stored as its value in the dictionary split_dict 98 | return ent_dict, split_dict 99 | 100 | 101 | def parent_node(dictionary, entropy): 102 | gain = {} 103 | for k,v in dictionary.items(): 104 | gain[k] = entropy - v 105 | attribute = max(gain, key=gain.get) 106 | return attribute, gain[attribute] 107 | 108 | def split_data(data, attribute, split_dict): 109 | left = data[data[attribute] <= split_dict[attribute]] 110 | right = data[data[attribute] > split_dict[attribute]] 111 | return left, right 112 | 113 | 114 | def unique_values(data1, data2): 115 | left_count = 0 116 | right_count = 0 117 | for i in (0,len(data1.columns)-1): 118 | left_idx = len(data1[data1.columns[i]].unique()) 119 | left_count = left_count + left_idx 120 | for i in (0,len(data2.columns)-1): 121 | right_idx = len(data2[data2.columns[i]].unique()) 122 | right_count = right_count + right_idx 123 | return left_count, right_count 124 | 125 | 126 | 127 | def complete_tree(data, keys): #This function is used to store the rules/decisions in an object through a class called "classifier" 128 | entropy, count = entropy_cal(data,keys) #The entropy of parent node is stored in the variable "entropy" 129 | ent_dict, split_dict = entropy_data(data, keys) 130 | attribute, gain = parent_node(ent_dict, entropy) #the attribute and gain is stored using the function parent_node 131 | if gain > 0: #An if loop is executed when the gain will be positive 132 | left, right = split_data(data, attribute, split_dict) #split_data function is used to split the dataset into two based on the attribute and split value 133 | left_count, right_count = unique_values(left, right) #the count of unique values from each attribute is calculated 134 | if left_count > len(left.columns) - 1: #if each attribute has only one value, then the if loop is not executed 135 | true = complete_tree(left, keys) 136 | if right_count > len(right.columns) - 1: 137 | false = complete_tree(right, keys) 138 | if left_count > len(left.columns) - 1 and right_count > len(right.columns) - 1: 139 | return classifier(true=true, false=false, column = attribute, split = split_dict[attribute]) #the attribute and split value is stored in the class 140 | else: 141 | return classifier(result = dict(zip(keys, count))) #the count of each class at the leaf node is stored as results in a class 142 | else: 143 | return classifier(result = dict(zip(keys, count))) 144 | 145 | a=complete_tree(data,keys) 146 | 147 | keys = key_labels(data) 148 | 149 | a = complete_tree(data,keys) 150 | 151 | 152 | ################################################################### 153 | #BUILDING THE MODEL# 154 | 155 | ################################################################# 156 | 157 | from sklearn.model_selection import train_test_split 158 | 159 | train, test = train_test_split(data, test_size=0.25) 160 | 161 | test22 = test.iloc[:, :-1] 162 | 163 | test_data = test22.to_dict('records') 164 | 165 | #test['result']="" 166 | 167 | 168 | 169 | 170 | #type(test_data) 171 | 172 | 173 | def traverse(a, each_row): 174 | if(a.column == -1): 175 | return max(a.result.iteritems(), key=operator.itemgetter(1))[0] 176 | if(each_row[a.column] < a.split ): 177 | return traverse(a.true, each_row) 178 | else: 179 | return traverse(a.false, each_row) 180 | 181 | for each_row in test_data: 182 | label_value = traverse(a, each_row) 183 | each_row['Label'] = label_value 184 | 185 | test_data2 = pd.DataFrame(test_data) 186 | 187 | labels_test_data= test_data2[test_data2.columns[[2]]] 188 | 189 | labels_of_original = test[test.columns[[-1]]] 190 | 191 | count=0 192 | for i in range(0,len(labels_test_data)): 193 | if labels_test_data.iloc[i,0] == labels_of_original.iloc[i,0]: 194 | count = count + 1 195 | count 196 | 197 | 198 | 199 | 200 | 201 | 202 | 203 | 204 | 205 | 206 | 207 | 208 | 209 | 210 | 211 | 212 | 213 | 214 | 215 | 216 | 217 | 218 | 219 | 220 | 221 | 222 | 223 | 224 | 225 | 226 | 227 | 228 | 229 | 230 | 231 | -------------------------------------------------------------------------------- /NLP.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python3 2 | # -*- coding: utf-8 -*- 3 | """ 4 | Created on Fri Apr 13 22:57:59 2018 5 | 6 | @author: MyReservoir 7 | """ 8 | 9 | #ALDA Project- NLP 10 | 11 | import random 12 | import os 13 | import numpy as np 14 | import pandas as pd 15 | import treepredict as dt 16 | 17 | os.getcwd() 18 | os.chdir('/Users/MyReservoir/Desktop/CSC 522 PROJECT/') 19 | os.getcwd() 20 | 21 | import nltk 22 | from nltk.stem import WordNetLemmatizer, PorterStemmer 23 | from nltk.tokenize import RegexpTokenizer, word_tokenize 24 | from pandas import DataFrame 25 | 26 | 27 | no_of_records=4000 28 | no_of_trials=10 29 | # ----- FUNCTIONS ------ 30 | 31 | # Data Preprocessing functions 32 | 33 | def nltk_process(sample_text): 34 | #reading an input text file 35 | #input_file = open('/Users/jagadeesh/PycharmProjects/ALDA/testdoc.txt','r') 36 | #sample_text = input_file.read() 37 | #input_file.close() 38 | 39 | 40 | #word tokenizer, but it includes the punctuation 41 | #tokenized = word_tokenize(sample_text) 42 | #tokenizing words using RegexpTokenizer of nltk, which by default removes all punctuation. 43 | tokenizer = RegexpTokenizer(r'\w+') 44 | tokenized = tokenizer.tokenize(sample_text) 45 | length_input = len(tokenized) #used later in for loop which splits pos_tags 46 | 47 | # print(tokenized) 48 | #converted each word to its root word using WordNetLemmatizer of nltk. 49 | lemma = WordNetLemmatizer() 50 | lemma_words = map(lemma.lemmatize, tokenized) 51 | pos_tagged = [] 52 | 53 | #function for assigning pos_tags 54 | def pos_tagging(): 55 | try: 56 | for i in lemma_words: 57 | words = nltk.word_tokenize(i) 58 | for j in words: 59 | tagged = nltk.pos_tag(words) 60 | pos_tagged.append(tagged) 61 | except Exception as e: 62 | print(str(e)) 63 | 64 | #function call for performing pos_tags 65 | pos_tagging() 66 | #print(pos_tagged) 67 | #splitting the pos_tags into two seperate lists for further processing 68 | list_df = DataFrame.from_records(pos_tagged) 69 | words = [] 70 | pos_final = [] 71 | for i in range(0, length_input): 72 | for j in range(0,2): 73 | if j == 0: 74 | words.append(list_df[0][i][j]) 75 | if j == 1: 76 | pos_final.append(list_df[0][i][j]) 77 | #print(words) 78 | #print(pos_final) 79 | 80 | #converted as table if required for further processing 81 | pos_table = np.column_stack((words, pos_final)) 82 | #pos_table=pd.DataFrame(words,pos_final) 83 | return pos_table 84 | 85 | def ads(st): 86 | merge = pd.merge(st, pd.DataFrame(dic), how='left', left_on='Word', right_on='Token', sort=False) 87 | merge = merge.fillna(0) 88 | merge2 = pd.merge(merge, pd.DataFrame(intense), how='left', left_on='Word', right_on='Token', sort=False) 89 | merge2 = merge2.fillna(0) 90 | 91 | for i in range(len(merge2.index)-1): 92 | merge2['Polarity_x'][i+1]=merge2['Polarity_x'][i+1]*(1+merge2['Polarity_y'][i]) 93 | 94 | merge3 = pd.merge(merge2, pd.DataFrame(bucket), how='left', left_on='POS', right_on='POS', sort=False) 95 | merge4 = pd.DataFrame(merge3.groupby(by = ['Bucket']).agg({'Polarity_x' : 'sum'}).transpose()) 96 | 97 | return merge4 98 | 99 | #Classification code 100 | #Define function to split dataset with ratio 101 | def splitDataset(dataset, splitRatio): 102 | trainSize = int(len(dataset) * splitRatio) 103 | trainSet = [] 104 | copy = dataset.values.tolist() 105 | while len(trainSet) < trainSize: 106 | index = random.randrange(len(copy)) 107 | trainSet.append(copy.pop(index)) 108 | return [trainSet, copy] 109 | 110 | 111 | # Data Preprocessing 112 | data = pd.read_csv('/Users/MyReservoir/Desktop/CSC 522 PROJECT/tweetylabel.csv',encoding ='utf=8') 113 | dic = pd.read_csv('/Users/MyReservoir/Desktop/CSC 522 PROJECT/dic.csv',encoding ='utf=8') 114 | intense = pd.read_csv('/Users/MyReservoir/Desktop/CSC 522 PROJECT/intense.csv',encoding ='utf=8') 115 | bucket = pd.read_csv('/Users/MyReservoir/Desktop/CSC 522 PROJECT/bucket.csv',encoding ='utf=8') 116 | 117 | data=data[:no_of_records] 118 | data.columns = ['Tweet','Sentiment'] 119 | 120 | output_nltk = [] 121 | for i in range(len(data)): 122 | sample_text = data['Tweet'][i] 123 | output = nltk_process(sample_text) 124 | output_nltk.append(output) 125 | 126 | ads_df = pd.DataFrame({'Adjective':[],'Adverb':[],'Noun':[],'Verb':[]}) 127 | 128 | for i in range(len(output_nltk)): 129 | nltkout_temp = pd.DataFrame(output_nltk[i]) 130 | #nltkout_temp = pd.DataFrame(sample_tweet) 131 | nltkout_temp.columns = ['Word','POS'] 132 | nltkout_temp['Word'] = pd.DataFrame(nltkout_temp['Word'].str.lower()) 133 | ads_df = ads_df.append(ads(nltkout_temp)) 134 | ads_df = ads_df.fillna(0) 135 | 136 | ads_df['index'] = range(1, len(ads_df) + 1) 137 | data['index'] = range(1, len(data) + 1) 138 | #data['label'] = data.apply(f,axis=1) 139 | ads_df_final = pd.merge(ads_df, pd.DataFrame(data), how='left', left_on='index', right_on='index', sort=False) 140 | dataset = ads_df_final[['Adjective','Adverb','Noun','Verb','Sentiment']] 141 | 142 | 143 | 144 | ############# Splitting the Dataset into Testing and Training Sets ############## 145 | final_acc=0.0 146 | 147 | for i in range(no_of_trials): 148 | splitRatio = 0.7 149 | trainingSet, testSet = splitDataset(dataset, splitRatio) 150 | #print(trainingSet) 151 | # print(type(trainingSet)) 152 | print('Split {0} rows into train = {1} and test = {2} rows'.format(len(dataset),len(trainingSet),len(testSet))) 153 | 154 | ############# Model Building ############## 155 | b = dt.buildtree(trainingSet) 156 | dt.drawtree(b,jpeg='treeview.jpg') 157 | 158 | #print("original_testset=",testSet) 159 | ############# Preparing Testing DataSet ############## 160 | testlabels=[] 161 | for i in range(len(testSet)): 162 | label=testSet[i].pop(-1) 163 | testlabels.append(label) 164 | 165 | #print("testSet=",testSet) 166 | #print("testlabels=",testlabels) 167 | ############# Classification of Test Records ############## 168 | number = 0 169 | for i in range(len(testSet)): 170 | #print("\ntest_data",testSet[i]) 171 | a = dt.classify(testSet[i], b) 172 | #print("a=",a) 173 | max=0 174 | best="" 175 | for key in a.keys(): 176 | if a[key]>max: 177 | max=a[key] 178 | best=key 179 | #print("best=",best) 180 | #print("label=",testlabels[i]) 181 | if(best == testlabels[i]): 182 | number = number + 1 183 | 184 | ############# Accuracy Calculations ############## 185 | accuracy = (number/len(testSet))* 100 186 | final_acc+=accuracy 187 | 188 | final_acc=final_acc/no_of_trials 189 | print('Accuracy: {0}%'.format(final_acc)) -------------------------------------------------------------------------------- /Poster Sentiment Analysis by Combining Lexicon-based and Machine Learning Methods - CSC 522 Project-page-001.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/rsher60/Sentiment-Analysis-by-combining-Machine-Learning-and-Lexicon-Based-methods/22f9553b20bce7f4fad599b44e89ec62fe2c9024/Poster Sentiment Analysis by Combining Lexicon-based and Machine Learning Methods - CSC 522 Project-page-001.jpg -------------------------------------------------------------------------------- /Poster Sentiment Analysis by Combining Lexicon-based and Machine Learning Methods - CSC 522 Project.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/rsher60/Sentiment-Analysis-by-combining-Machine-Learning-and-Lexicon-Based-methods/22f9553b20bce7f4fad599b44e89ec62fe2c9024/Poster Sentiment Analysis by Combining Lexicon-based and Machine Learning Methods - CSC 522 Project.pdf -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Sentiment-Analysis-by-combining-Machine-Learning-and-Lexicon-Based-methods 2 | This project is on twitter sentimental analysis by combining lexicon based and machine learning approaches. A supervised lexicon-based approach for extracting sentiments from tweets was implemented. Various supervised machine learning approaches were tested using scikit-learn libraries in python and implemented Decision Trees and Naive Bayes techniques. 3 | 4 | The entire code for preprocessing, implementation and post-processing of the project was done in Python 2.7. 5 | 6 | ## Overview of the Project 7 | 8 | 9 | 10 | 11 | 12 | ## Requirements 13 | The packages required for running the code are listed below. 14 | * Sklearn 15 | * Pandas 16 | * Numpy 17 | * Math 18 | * io 19 | * os 20 | * Nltk 21 | 22 | 23 | ## Installations 24 | Most of the packages can be installed using normal pip commands. Installing NLTK may require special instructions which can be found at https://www.nltk.org/install.html 25 | 26 | The preprocessing files which are required to run the code are as follows: 27 | 28 | 1. tweetylabel.csv #contains the input tweets 29 | 2. dic.csv #contains the dictionary created and merged 30 | 3. intense.csv. #contains the intensifiers 31 | 4. bucket.csv. #creates the bucket 32 | 5. positive-words.txt #contains the positive word list as text file 33 | 6. negabuse.txt #contains the negative and abusive word list as text file 34 | 35 | 36 | ## Instruction for running the code 37 | 38 | Keep all the above mentioned preprocessing files in the same folder and change the directory to that folder. lexi_plus_ml.py file contains the entire code for the project. Open the code and specify the working directory on line 17 of the code. 39 | -------------------------------------------------------------------------------- /bucket.csv: -------------------------------------------------------------------------------- 1 | POS,Bucket 2 | NN,Noun 3 | NNS,Noun 4 | NNP,Noun 5 | NNPS,Noun 6 | PRP$,Noun 7 | PRP,Noun 8 | WP,Noun 9 | WP$,Noun 10 | MD,Verb 11 | VB,Verb 12 | VBC,Verb 13 | VBD,Verb 14 | VBF,Verb 15 | VBG,Verb 16 | VBN,Verb 17 | VBP,Verb 18 | VBZ,Verb 19 | JJ,Adjective 20 | JJR,Adjective 21 | JJS,Adjective 22 | RB,Adverb 23 | RBR,Adverb 24 | RBS,Adverb 25 | WRB,Adverb 26 | -------------------------------------------------------------------------------- /dic.csv: -------------------------------------------------------------------------------- 1 | Token,Polarity 2 | (full)_of_PRP,-3 3 | abhorred,-5 4 | abhorrent,-5 5 | able,1 6 | abominable,-5 7 | above-average,2 8 | abrasive,-4 9 | absent,-1 10 | absorbing,4 11 | absurd,-3 12 | abundant,3 13 | abusive,-5 14 | abysmal,-4 15 | academic,1 16 | acceptable,1 17 | accessible,3 18 | acclaimed,4 19 | accord-based,1 20 | accurate,3 21 | acidic,-4 22 | acrid,-2 23 | acrimonious,-2 24 | action,1 25 | action-adventure,1 26 | action-packed,3 27 | active,2 28 | acute,-2 29 | adaptable,2 30 | addictive,2 31 | adept,3 32 | adequate,1 33 | adequate-borderline,1 34 | adjustable,2 35 | admirable,4 36 | adorable,5 37 | adored,4 38 | adroit,3 39 | adventurous,3 40 | adverse,-2 41 | aerodynamic,1 42 | affectionate,2 43 | affluent,3 44 | afraid,-3 45 | after-the-fact,-1 46 | age-old,1 47 | aggressive,-3 48 | aggrieved,-2 49 | aghast,-5 50 | agile,1 51 | agonizing,-5 52 | aimless,-1 53 | air-conditioned,3 54 | airy,2 55 | alarming,-2 56 | alcoholic,-1 57 | alien,-2 58 | alienated,-2 59 | all-around,1 60 | all-clear,1 61 | alleged,-2 62 | all-mighty,3 63 | all-new,2 64 | all-out,3 65 | allowable,1 66 | all-purpose,1 67 | all-star,5 68 | all-time,1 69 | all-too-rare,3 70 | all-weather,1 71 | all-you-can-eat,4 72 | almighty,3 73 | aloof,-1 74 | already-nice,2 75 | altruistic,4 76 | amateurish,-2 77 | amateurish-looking,-2 78 | amazing,5 79 | ambitious,-1 80 | ambivalent,-1 81 | amenity-poor,-3 82 | amicable,1 83 | amoral,-1 84 | ample,3 85 | amusing,3 86 | anal,-4 87 | anal-retentive,-4 88 | analytical,-1 89 | ancient,-1 90 | anemic,-3 91 | angelic,5 92 | angry,-3 93 | annoyed,-2 94 | annoying,-4 95 | antagonistic,-2 96 | anticipated,2 97 | anticlimactic,-3 98 | anticlimatic,-3 99 | anti-climatic,-3 100 | anti-glare,2 101 | anti-lock,2 102 | antipathetic,-2 103 | antique,1 104 | anxious,-2 105 | apocalyptic,-5 106 | apologetic,-1 107 | appalled,-4 108 | appalling,-5 109 | apparent,-1 110 | appealing,3 111 | appreciative,3 112 | apprehensive,-2 113 | appropriate,1 114 | apt,2 115 | arbitrary,-2 116 | archetypal,1 117 | arresting,2 118 | arrogant,-3 119 | artful,3 120 | artificial,-1 121 | artistic,3 122 | artistical,2 123 | artsy,1 124 | ashamed,-3 125 | asinine,-3 126 | as-is,-1 127 | aspiring,1 128 | assertive,1 129 | ass-kicking,3 130 | asthmatic,-1 131 | astonishing,3 132 | astounding,3 133 | astronomically-priced,-5 134 | astute,3 135 | attentive,2 136 | attractive,3 137 | auspicious,2 138 | austere,1 139 | authentic,1 140 | authoritarian,-4 141 | auto-focus,1 142 | automatic,1 143 | automatically-bestselling,1 144 | autorcratic,-2 145 | auto-tilting,1 146 | auxiliary,1 147 | available,3 148 | average,1 149 | averaged-sized,1 150 | average-good,1 151 | average-sized,1 152 | avid,2 153 | awesome,5 154 | awestruck,5 155 | awkward,-3 156 | awry,-2 157 | baked-on,-3 158 | balanced,1 159 | balky,-2 160 | banal,-4 161 | bang-up,2 162 | bankrupt,-3 163 | barbaric,-3 164 | barbarous,-3 165 | bare,-1 166 | barren,-2 167 | baseless,-2 168 | base-level,-1 169 | bearable,-1 170 | beastly,-3 171 | beauteous,4 172 | beautiful,4 173 | beefy,-1 174 | believable,1 175 | believeable,2 176 | bellicose,-3 177 | belligerent,-4 178 | beloved,4 179 | beneficial,1 180 | benevolent,4 181 | benign,1 182 | berserk,-2 183 | best-drawn,5 184 | best-handling,5 185 | bestselling,5 186 | best-selling,3 187 | better-feeling,4 188 | better-like,4 189 | better-than-before,4 190 | bewildered,-2 191 | b-grade,-3 192 | big-breasted,-1 193 | big-hearted,2 194 | big-time,2 195 | bitchy,-3 196 | bite-sized,1 197 | bitter,-2 198 | bittersweet,-1 199 | bizarre,-3 200 | black-market,-2 201 | blameless,1 202 | blameworthy,-2 203 | bland,-2 204 | blander-than-bland,-2 205 | blank,-1 206 | blasphemous,-4 207 | blatant,-3 208 | bleak,-3 209 | bleary-eyed,-2 210 | blind,-3 211 | blinding,-3 212 | blissful,4 213 | bloated,-3 214 | bloody,-2 215 | blunt,-1 216 | boastful,-1 217 | bogus,-2 218 | boisterous,2 219 | bold,3 220 | bone-headed,-3 221 | bonkers,-3 222 | book-lined,1 223 | booted,-2 224 | booze-and-puke,-4 225 | borderless,3 226 | borderline,-1 227 | bored,-3 228 | boresome,-3 229 | boring,-3 230 | bothersome,-3 231 | bouncy,1 232 | boxy,-1 233 | boy-bait,-3 234 | brainless,-3 235 | brain-racking,-1 236 | brand-new,4 237 | brand-spankin,4 238 | brand-spankin'-new,4 239 | brash,-2 240 | brassy,-3 241 | brave,-1 242 | brazen,-3 243 | break-in,-4 244 | breathless,2 245 | breathtaking,5 246 | breath-taking,5 247 | brief,-1 248 | bright,3 249 | brilliant,5 250 | brittle,-3 251 | broken,-3 252 | brusque,-1 253 | brutal,-5 254 | brutish,-3 255 | bubble-butt,-5 256 | bubbly,2 257 | buck-toothed,-1 258 | budget-conscious,2 259 | buff,3 260 | buggy,-3 261 | built-in,2 262 | built-to-last,3 263 | bulky,-2 264 | bumpy,-1 265 | burdensome,-2 266 | businesslike,-1 267 | busted,-2 268 | busy,-1 269 | byzantine,-2 270 | cafeteria-style,-1 271 | cafeteria-type,-1 272 | calm,2 273 | calumnious,-4 274 | campy,-1 275 | cancerous,-4 276 | canned,-3 277 | canned-tasting,-3 278 | capable,2 279 | capacious,2 280 | capricious,-2 281 | captivating,3 282 | careful,1 283 | careless,-1 284 | casual,1 285 | catastrophic,-5 286 | catatonic,-2 287 | catchy,2 288 | cathartic,2 289 | caustic,-3 290 | cautious,-1 291 | cavernous,1 292 | c-class,-1 293 | celestial,1 294 | central,1 295 | ceremonial,1 296 | challenging,1 297 | chaotic,-2 298 | character-driven,1 299 | characterless,-2 300 | charismatic,3 301 | charitable,1 302 | charming,4 303 | cheap-o,-4 304 | cheeky,-3 305 | cheerful,3 306 | cheerless,-2 307 | cheery,1 308 | cheesy,-2 309 | cherubic,2 310 | chic,2 311 | childish,-3 312 | childlike,-1 313 | child-like,-1 314 | chilly,-1 315 | chintzy,-2 316 | chivalrous,2 317 | choppy,-1 318 | chronic,-3 319 | chubby,-2 320 | chuckle-worthy,2 321 | chummy,1 322 | chunky,-2 323 | civil,1 324 | civilized,1 325 | classical,1 326 | classy,3 327 | clean,2 328 | clear-bodied,2 329 | clear-cut,3 330 | clever,3 331 | clich?d,-2 332 | cliched,-3 333 | cliff-hanging,2 334 | climactic,2 335 | climate-control,1 336 | clinical,-1 337 | cloudless,1 338 | cloudy,-1 339 | cloying,-2 340 | clueless,-2 341 | clumsy,-2 342 | clunky,-2 343 | coarse,-2 344 | cocky,-2 345 | 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| cumbersome,-2 453 | cursed,-3 454 | cursory,-2 455 | curt,-1 456 | customary,1 457 | cute,3 458 | cutesy,-1 459 | cut-rate,2 460 | cutthroat,-2 461 | cynical,-3 462 | dainty,1 463 | damaging,-4 464 | danceable,1 465 | dandy,3 466 | dangerous,-3 467 | darker-and-funnier-than-expected,4 468 | darn,-2 469 | dashing,3 470 | dated,-1 471 | daunting,-2 472 | dazzled,3 473 | dazzling,5 474 | deadly,-1 475 | dear,3 476 | debatable,-1 477 | debilitating,-3 478 | decadent,5 479 | deceitful,-1 480 | decent,1 481 | decent-sized,2 482 | decisive,1 483 | decorative,2 484 | decrepit,-3 485 | dedicated,2 486 | defective,-3 487 | defensive,-1 488 | defiant,-3 489 | deficient,-3 490 | deformed,-2 491 | deft,3 492 | defunct,-1 493 | degrading,-2 494 | dejected,-2 495 | delicate,2 496 | delicious,5 497 | delighted,4 498 | delightful,5 499 | deluded,-4 500 | delusional,-5 501 | deluxe,5 502 | demeaning,-3 503 | dense,-3 504 | dependable,3 505 | dependent,-1 506 | deplorable,-5 507 | depraved,-5 508 | 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| high-up,1 1001 | hilarious,4 1002 | hi-larious,1 1003 | hip,2 1004 | historic,1 1005 | hit-making,4 1006 | ho-hum,-1 1007 | hollow,-2 1008 | holy,4 1009 | home-cooked,2 1010 | homeless,-1 1011 | home-made,1 1012 | honest,2 1013 | honorable,2 1014 | hopeful,2 1015 | hopeless,-2 1016 | hopped-up,-1 1017 | horny,-2 1018 | horrendous,-5 1019 | horrible,-5 1020 | horrid,-5 1021 | horrific,-5 1022 | horrifying,-5 1023 | horror,-3 1024 | hospitable,3 1025 | hostile,-4 1026 | hot,1 1027 | hubristic,-2 1028 | human,2 1029 | humane,2 1030 | humanistic,1 1031 | humble,2 1032 | humid,-2 1033 | humiliating,-4 1034 | humongous,1 1035 | humorous,3 1036 | hungry,-2 1037 | hurtful,-3 1038 | hushed,-3 1039 | hyperactive,-1 1040 | hyperkinetic,2 1041 | hypersensitive,-1 1042 | hypnotic,1 1043 | hypocritical,-3 1044 | hysterical,3 1045 | icy,-2 1046 | ideal,4 1047 | idealistic,-1 1048 | idiotic,-4 1049 | idle,-1 1050 | idyllic,4 1051 | ignorant,-3 1052 | ill-advised,-3 1053 | ill-conceived,-2 1054 | 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inevitable,-1 1149 | inexcusable,-4 1150 | inexhaustible,2 1151 | inexorable,-2 1152 | inexpensive,3 1153 | inexperienced,-1 1154 | inexplicable,-1 1155 | inexpressible,-1 1156 | inextricable,-1 1157 | infallible,3 1158 | infamous,-2 1159 | infantile,-3 1160 | infectious,2 1161 | inferior,-3 1162 | infernal,-3 1163 | infertile,-2 1164 | infested,-4 1165 | infirme,-1 1166 | inflexible,-2 1167 | in-flight,-2 1168 | influential,2 1169 | informal,1 1170 | informative,2 1171 | infuriated,-4 1172 | ingenious,4 1173 | ingenuous,-2 1174 | ingratiating,2 1175 | inhospitable,-2 1176 | inhumane,-3 1177 | innocent,2 1178 | innocuous,1 1179 | innovative,4 1180 | inoffensive,1 1181 | inoperable,-2 1182 | inoperative,-2 1183 | inopportune,-1 1184 | inprudent,-1 1185 | inpudent,-3 1186 | inquisitive,1 1187 | in-room,3 1188 | insane,-3 1189 | insecure,-2 1190 | insidious,-4 1191 | insightful,3 1192 | insincere,-2 1193 | insolent,-3 1194 | insolvent,-3 1195 | inspirational,3 1196 | instructional,3 1197 | insubstantial,-1 1198 | insufferable,-4 1199 | insufficient,-1 1200 | insulted,-2 1201 | insulting,-4 1202 | insurmountable,-3 1203 | intact,1 1204 | intangible,1 1205 | intellectual,3 1206 | intelligent,4 1207 | intense,3 1208 | intensive,2 1209 | intentional,-1 1210 | interesting,3 1211 | interference-free,3 1212 | interminable,-3 1213 | intermittent,-1 1214 | international-gourmet,4 1215 | intimate,1 1216 | intolerable,-4 1217 | intoxicated,-1 1218 | intoxicating,2 1219 | intractible,-2 1220 | intricate,1 1221 | intriguing,3 1222 | introspective,1 1223 | intrusive,-2 1224 | intuitive,3 1225 | in-tune,3 1226 | invaluable,4 1227 | invasive,-2 1228 | invective,-3 1229 | inventive,3 1230 | invidious,-3 1231 | invincible,1 1232 | invisible,1 1233 | inviting,3 1234 | invulnerable,4 1235 | in-your-face,-3 1236 | irate,-3 1237 | ironic,-2 1238 | irrational ,-2 1239 | irreconcilable,-2 1240 | irredeemable,-4 1241 | irrefutable,2 1242 | irregular,-1 1243 | irrelevant,-1 1244 | 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| latest,1 1298 | laughable,-2 1299 | laugh-out-loud,3 1300 | lavish,4 1301 | law-abiding,1 1302 | lax,-2 1303 | lazy,-2 1304 | leaden,-2 1305 | leading,3 1306 | lean,-1 1307 | least_favorite,-3 1308 | leather-wrapped,3 1309 | lecherous,-3 1310 | legal,1 1311 | legendary,4 1312 | legible,1 1313 | legitimate,1 1314 | leisurely,2 1315 | lengthy,-1 1316 | lenient,1 1317 | lesser-known,-1 1318 | less-expensive,1 1319 | less-than-desireable,-2 1320 | less-than-reliable,-2 1321 | less-than-substantial,-2 1322 | lethal,-4 1323 | lethargic,-1 1324 | letter-perfect,3 1325 | lewd,-2 1326 | liberal,2 1327 | licentious,-2 1328 | lifeless,-4 1329 | lifelike,3 1330 | lighthearted,2 1331 | light-hearted,2 1332 | lightning-fast,3 1333 | lightweight,1 1334 | light-weight,3 1335 | likable,2 1336 | likeable,2 1337 | lilliputian,-2 1338 | limited,-1 1339 | line-up,-3 1340 | lint-free,3 1341 | lionhearted,1 1342 | listenable,2 1343 | literate,2 1344 | liveable,1 1345 | lively,3 1346 | liven-up,3 1347 | 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maddening,-2 1402 | magical,4 1403 | magnetic,2 1404 | magnificent,5 1405 | majestic,4 1406 | maladjusted,-2 1407 | malcontent,-2 1408 | malcontented,-2 1409 | malevolent,-4 1410 | malicious,-4 1411 | malignant,-4 1412 | malodorous,-3 1413 | manageable,1 1414 | manipulative,-3 1415 | manly,1 1416 | marginal,-1 1417 | marvellous,5 1418 | marvelous,5 1419 | masochistic,-3 1420 | mass-market,-1 1421 | mass-marketed,-1 1422 | master-chef,3 1423 | masterful,4 1424 | masterly,3 1425 | matchless,4 1426 | materialistic,-1 1427 | maternal,1 1428 | matronly,-2 1429 | mature,1 1430 | maximum,1 1431 | meandering,-2 1432 | meaningful,3 1433 | meaningless,-3 1434 | mean-spirited,-3 1435 | meaty,2 1436 | mediocre,-2 1437 | mega-star,3 1438 | mega-success,5 1439 | melancholic,-1 1440 | mellow,1 1441 | melodic,2 1442 | melodramatic,-2 1443 | melted-looking,-3 1444 | memorable,3 1445 | menacing,-3 1446 | menial,-3 1447 | merciless,-3 1448 | mere,-2 1449 | merry,2 1450 | mesmerizing,4 1451 | messy,-2 1452 | meticulous,1 1453 | middling-to-weak,-1 1454 | mid-line,-1 1455 | mid-range,-1 1456 | mighty,1 1457 | mind-blowing,2 1458 | mind-boggling,-1 1459 | mindless,-2 1460 | mind-numbing,-3 1461 | mini-conflict,-1 1462 | minimal,-1 1463 | minimum,-1 1464 | miraculous,4 1465 | misbegotten,-1 1466 | mischievous,-2 1467 | miserable,-5 1468 | misguided,-2 1469 | mish,-2 1470 | mish-mash,-2 1471 | mis-match,-2 1472 | misogynistic,-3 1473 | mistaken,-2 1474 | moderately-priced,1 1475 | modern,2 1476 | modest,1 1477 | modular,2 1478 | moldy,-3 1479 | momentous,4 1480 | money-hungry,-3 1481 | monolithic,-1 1482 | monotone,-2 1483 | monotonous,-3 1484 | monstrous,-4 1485 | moody,-1 1486 | moot,-1 1487 | moralistic,-1 1488 | morbid,-3 1489 | moronic,-3 1490 | morose,-2 1491 | mortifying,-4 1492 | mournful,-4 1493 | mouth-watering,5 1494 | moving,3 1495 | much-admired,4 1496 | much-used,1 1497 | muddy,-2 1498 | multi-dimensional,2 1499 | multi-faceted,2 1500 | multi-task,3 1501 | multi-tasking,3 1502 | multi-tasks,3 1503 | murderous,-4 1504 | murky,-1 1505 | muscular,3 1506 | mushy,-1 1507 | musical,3 1508 | must-have,4 1509 | mystic,1 1510 | mystical,2 1511 | naive,-2 1512 | naked,-2 1513 | nameless,-2 1514 | narrow,-1 1515 | nasal,-1 1516 | nasty,-5 1517 | native,1 1518 | natural,2 1519 | naughty,-1 1520 | nauseating,-3 1521 | nauseous,-4 1522 | near-classic,3 1523 | near-cult,3 1524 | near-perfect,4 1525 | near-pornographic,-3 1526 | near-silence,2 1527 | neat,2 1528 | neat-freak,-1 1529 | needless,-1 1530 | needy,-1 1531 | nefarious,-3 1532 | negligent,-2 1533 | negligible,-2 1534 | nerd-like,-1 1535 | nerdy,-1 1536 | nervous,-1 1537 | neurotic,-3 1538 | new,2 1539 | new-classic,1 1540 | newfound,1 1541 | new-this-year,3 1542 | nice-looking,2 1543 | nicely-tuned,2 1544 | nice-sounding,2 1545 | nifty,2 1546 | nihilistic,-1 1547 | nimble,1 1548 | nit-picky,-2 1549 | noble,2 1550 | no-frills,-1 1551 | no-holds-barred,1 1552 | noisy,-2 1553 | non-adjustable,-2 1554 | no-name,-2 1555 | non-calibrated,-2 1556 | nonchalant,-1 1557 | non-communicative,-2 1558 | non-corrosive,3 1559 | non-descript,-1 1560 | non-existant,-2 1561 | nonexistent,-2 1562 | non-existent,-2 1563 | non-functional,-3 1564 | non-functioning,-3 1565 | non-gourmet,-1 1566 | no-no,-2 1567 | non-proprietary,3 1568 | nonsensical,-2 1569 | non-skid,3 1570 | non-slip,3 1571 | non-smoking,1 1572 | non-stick,3 1573 | non-sticks,3 1574 | non-traditional,3 1575 | no-questions-asked,3 1576 | normal,2 1577 | nostalgic,2 1578 | nosy,-2 1579 | not_(bad),2 1580 | not_enough,-2 1581 | notable,1 1582 | notchy,-2 1583 | noteable,1 1584 | noteworthy,2 1585 | notorious,-4 1586 | not-quite-mediocre,-2 1587 | not-too-subtle,-2 1588 | nourishing,2 1589 | novel,1 1590 | numb,-2 1591 | nurturing,2 1592 | oafish,-2 1593 | obligatory,-2 1594 | oblivious,-3 1595 | obnoxious,-3 1596 | obscene,-4 1597 | obselete,-3 1598 | observant,1 1599 | obsessive,-3 1600 | obsolete,-3 1601 | obstinate,-1 1602 | obsure,-1 1603 | obtainable,1 1604 | obtrusive,-1 1605 | obtuse,-1 1606 | odd,-1 1607 | offbeat,1 1608 | off-cambered,-1 1609 | off-center,-1 1610 | offended,-2 1611 | offensive,-2 1612 | offhand,-1 1613 | official,1 1614 | off-point,-1 1615 | ok,1 1616 | okay,1 1617 | old,-1 1618 | old-fashioned,-1 1619 | old-hat,-1 1620 | old-school,-1 1621 | old-soul,-1 1622 | ominous,-3 1623 | one-dimensional,-2 1624 | one-note,-2 1625 | one-of-a-kind,3 1626 | one-on-one,1 1627 | onerous,-3 1628 | one-sided,-2 1629 | one-track,-2 1630 | operational,1 1631 | operative,1 1632 | opportune,1 1633 | opressive,-3 1634 | optimal,2 1635 | optimistic,2 1636 | optimum,4 1637 | optional,1 1638 | opulent,4 1639 | organic,3 1640 | orgasmic,5 1641 | original,1 1642 | ornate,2 1643 | ornery,-2 1644 | oscar-winning,4 1645 | oscar-worthy,5 1646 | ostentatious,-1 1647 | otherworldly,3 1648 | outdated,-2 1649 | outgoing,2 1650 | outlandish,-3 1651 | outmoded,-2 1652 | out-of-it,-1 1653 | out-perform,3 1654 | outraged,-4 1655 | outrageous,-1 1656 | outspoken,-1 1657 | outstanding,5 1658 | oven-proof,2 1659 | oven-safe,2 1660 | over-acting,-3 1661 | overblown,-2 1662 | over-boosted,-1 1663 | over-developed,-1 1664 | over-done,-2 1665 | overdrive,-1 1666 | overdue,-2 1667 | over-engineered,-2 1668 | overgrown,-2 1669 | over-played,-2 1670 | over-powerful,-2 1671 | over-priced,-3 1672 | over-rated,-3 1673 | oversimplified,-1 1674 | oversized,-2 1675 | over-spiritualized,-2 1676 | over-the-top,-3 1677 | overweight,-2 1678 | overwhelming,-1 1679 | over-whelming,-1 1680 | overworked,-2 1681 | overwrought,-3 1682 | overzealous,-2 1683 | padlockable,3 1684 | painful,-4 1685 | painless,1 1686 | painstaking,-3 1687 | palatable,1 1688 | pale,-1 1689 | paltry,-2 1690 | pampered,4 1691 | panicky,-2 1692 | panoramic,5 1693 | paper-thin,-1 1694 | papery,-1 1695 | paranoid,-2 1696 | parasitic,-3 1697 | passionate,3 1698 | passive-agressive,-1 1699 | pastoral,2 1700 | paternal,-1 1701 | pathetic,-4 1702 | pathological,-4 1703 | patient,3 1704 | patriarchal,-2 1705 | patriotic,1 1706 | peaceful,4 1707 | peculiar,-2 1708 | pedantic,-4 1709 | pedestrian,-2 1710 | peerless,5 1711 | peevish,-1 1712 | penetrating,3 1713 | peppy,2 1714 | perfect,5 1715 | perfidious,-4 1716 | performance-oriented,1 1717 | perfunctory,-1 1718 | pernicious,-3 1719 | perplexed,-2 1720 | persistent,-2 1721 | personable,2 1722 | persuasive,1 1723 | pertinent,1 1724 | perturbed,-2 1725 | pervasive,-1 1726 | perverse,-4 1727 | pessimistic,-1 1728 | petty,-2 1729 | petulant,-1 1730 | pgnacious,-3 1731 | phenomenal,5 1732 | phony,-3 1733 | piano-blessed,5 1734 | piano-heavy,-1 1735 | picky,-2 1736 | pinched,-2 1737 | pint-sized,-1 1738 | pithy,2 1739 | pitiable,-3 1740 | pitiful,-4 1741 | plasticky,-1 1742 | plausible,1 1743 | playable,2 1744 | playful,2 1745 | pleasant,4 1746 | pleasing,4 1747 | plebian,-1 1748 | plentiful,2 1749 | plodding,-3 1750 | plucky,2 1751 | plug-and-play,3 1752 | plush,1 1753 | poetic,3 1754 | poignant,4 1755 | pointless,-4 1756 | poisonous,-2 1757 | polished,2 1758 | polite,2 1759 | political,-1 1760 | poor,-2 1761 | popular,3 1762 | porky-looking,-3 1763 | pornographic,-4 1764 | portable,4 1765 | portly,-1 1766 | posh,2 1767 | positive,3 1768 | possible,1 1769 | potent,1 1770 | poverty-stricken,-1 1771 | powerful,3 1772 | powerless,-2 1773 | power-mad,-1 1774 | practical,1 1775 | preachy,-1 1776 | precious,3 1777 | precise,2 1778 | precision,1 1779 | predatory,-2 1780 | predictable,-2 1781 | preeminent,4 1782 | pre-eminent,4 1783 | preferable,1 1784 | prejudicial,-2 1785 | pre-owned,-1 1786 | pre-packaged,-1 1787 | preposterous,-4 1788 | preservative-laden,-3 1789 | prestigious,5 1790 | presumptuous,-1 1791 | pretentious,-3 1792 | pretty-boy,-3 1793 | prevalent,-1 1794 | priceless,5 1795 | prideful,-1 1796 | prim,-1 1797 | prime,1 1798 | primitive,-2 1799 | principled,2 1800 | pristine,4 1801 | priviledged,1 1802 | proactive,2 1803 | problematic,-3 1804 | problem-free,3 1805 | productive,1 1806 | profane,-4 1807 | professional,3 1808 | professional-looking,3 1809 | proficient,2 1810 | profitable,1 1811 | profound,4 1812 | programmable,2 1813 | progressive,2 1814 | prohibitive,-3 1815 | prolific,3 1816 | prolonged,-1 1817 | prominent,1 1818 | promiscuous,-2 1819 | promising,2 1820 | prompt,1 1821 | prone,-1 1822 | proper,1 1823 | properous,2 1824 | proprietary,-1 1825 | prosperous,2 1826 | protective,-1 1827 | proud,1 1828 | pseudo,-2 1829 | pseudo-intellectual,-1 1830 | psychopathic,-2 1831 | psychotic,-4 1832 | punchy,-2 1833 | punk,-2 1834 | puny,-4 1835 | puritan,-2 1836 | puritanical,-2 1837 | purposeful,2 1838 | pushy,-1 1839 | put-off,-2 1840 | puzzling,-1 1841 | quaint,2 1842 | quality,3 1843 | quarrelsome,-2 1844 | quasi-fascist,-4 1845 | quasi-luxury,1 1846 | queasy,-2 1847 | queen-sized,3 1848 | queer,-1 1849 | questionable,-1 1850 | quiet,1 1851 | quintessential,3 1852 | quirky,1 1853 | quite-boring,-2 1854 | rabid,-3 1855 | racist,-5 1856 | racy,2 1857 | radiant,4 1858 | radical,-1 1859 | ragged,-1 1860 | rain-soaked,-2 1861 | rainy,-1 1862 | rakish,-3 1863 | rambling,-1 1864 | rampant,-1 1865 | ramshackle,-2 1866 | rancid,-5 1867 | rank,-3 1868 | rapturous,5 1869 | rare,1 1870 | rash,-1 1871 | raspy,-1 1872 | rational,1 1873 | ratty,-1 1874 | raw,-1 1875 | readable,1 1876 | ready-to-pop,1 1877 | realistic,1 1878 | real-life,1 1879 | real-world,1 1880 | reasonable,1 1881 | recalcitrant,-2 1882 | receptive,1 1883 | reckless,-2 1884 | reclining,3 1885 | recognisable,1 1886 | recognizable,1 1887 | recommendable,3 1888 | record-setting,3 1889 | recoverable,1 1890 | red-blooded,-1 1891 | redeeming,1 1892 | redepemption,2 1893 | redundant,-1 1894 | refillable,3 1895 | refined,4 1896 | reflective,2 1897 | refreshing,4 1898 | regal,4 1899 | regretful,-2 1900 | regular,1 1901 | relaxing,1 1902 | relentless,-2 1903 | relevant,1 1904 | reliable,2 1905 | reliant,-1 1906 | religious,-1 1907 | reluctant,-1 1908 | remarkable,4 1909 | reminiscent,1 1910 | remorseless,-1 1911 | remote,-1 1912 | removable,4 1913 | renowned,3 1914 | repetitious,-1 1915 | repetitive,-1 1916 | replete,-1 1917 | reprehensible,-4 1918 | repressive,-3 1919 | reproachful,-2 1920 | repugnant,-4 1921 | repulsive,-5 1922 | reputable,3 1923 | resilient,2 1924 | resourceful,2 1925 | resource-heavy,-1 1926 | respectable,1 1927 | respectful,1 1928 | resplendent,4 1929 | responsible,1 1930 | responsive,1 1931 | restaurant-like,2 1932 | restful,1 1933 | restless,-1 1934 | resurgent,2 1935 | reticent,-1 1936 | revealing,-1 1937 | revengeful,-3 1938 | reviled,-4 1939 | revolting,-4 1940 | revolutionary,3 1941 | rewarding,3 1942 | rhythmic,3 1943 | rich,3 1944 | rickety,-3 1945 | ridiculous,-3 1946 | riff-raff,-3 1947 | right,1 1948 | righteous,-2 1949 | rigid,-1 1950 | ringed,-1 1951 | ripe,-1 1952 | rip-offs,-2 1953 | risky,-2 1954 | ritz-carlton,4 1955 | riveting,4 1956 | robot-sounding,-2 1957 | robust,2 1958 | rockin,3 1959 | rocky,-1 1960 | romantic,3 1961 | roomy,3 1962 | rosy,2 1963 | rough,-1 1964 | rousing,3 1965 | rowdy,-2 1966 | r-rated,-1 1967 | rubbery,-2 1968 | rude,-3 1969 | rugged,3 1970 | ruinous,-4 1971 | run-down,-2 1972 | rusted,-3 1973 | rustic,1 1974 | rustic-yet-contemporary,2 1975 | rust-prone,-3 1976 | rusty,-3 1977 | ruthless,-2 1978 | sacred,3 1979 | sad,-2 1980 | safe,1 1981 | sage,3 1982 | salacious,-3 1983 | saleable,1 1984 | salvageable,-1 1985 | sanctimonious,-3 1986 | sand-covered,2 1987 | sandy,2 1988 | sane,1 1989 | sanguine,1 1990 | sappy,-2 1991 | satanic,-5 1992 | satisfactory,1 1993 | satisfying,3 1994 | savage,-3 1995 | savory,3 1996 | savvy,2 1997 | scarce,-1 1998 | scared,-1 1999 | scary,-3 2000 | scathing,-4 2001 | scatological,-4 2002 | scenic,4 2003 | scheming,-3 2004 | schizophrenic,-3 2005 | scholarly,1 2006 | scientific,1 2007 | scrumptious,5 2008 | scrupulous,1 2009 | scummy,-2 2010 | seamless,3 2011 | second-rate,-2 2012 | second-skimmings,-2 2013 | secretive,-2 2014 | sedate,1 2015 | seductive,1 2016 | seedy,-3 2017 | seething,-4 2018 | see-through,-3 2019 | self-appointed,-1 2020 | self-congratulatory,-1 2021 | self-defeating,-2 2022 | self-described,-1 2023 | self-destructive,-2 2024 | self-hatred,-3 2025 | self-indulgent,-2 2026 | self-inflicted,-2 2027 | selfish,-3 2028 | self-mutilating,-3 2029 | self-respecting,1 2030 | self-righteous,-2 2031 | self-serving,-2 2032 | self-sufficient,2 2033 | selling-out,-2 2034 | sell-out,-2 2035 | senile,-3 2036 | sensational,5 2037 | senseless,-3 2038 | sensitive,1 2039 | sentimental,2 2040 | sequal,-1 2041 | serene,1 2042 | severe,-1 2043 | sex-and-booze-drenched,-3 2044 | sexual,1 2045 | sexy,4 2046 | shabby,-2 2047 | shady,-2 2048 | shaky,-2 2049 | shallow,-2 2050 | shameful,-3 2051 | shameless,-3 2052 | sharp,1 2053 | sharp-cornered,-3 2054 | sharp-tongued,-4 2055 | sheepish,-2 2056 | shifty,-1 2057 | shiny,1 2058 | shitty,-3 2059 | shocking,-1 2060 | shoddy,-3 2061 | shoeless,-2 2062 | short-lived,-1 2063 | showy,-1 2064 | shrewd,1 2065 | shrill,-3 2066 | shy,-1 2067 | sick,-3 2068 | sickening,-5 2069 | sickly,-3 2070 | significant,1 2071 | silent,2 2072 | silky,3 2073 | silly,-1 2074 | silver,1 2075 | simplistic,-1 2076 | sincere,2 2077 | sinful,-2 2078 | sinister,-3 2079 | sizable,1 2080 | sizzling,1 2081 | skeptical,-2 2082 | sketchy,-2 2083 | skilful,2 2084 | skilled,2 2085 | skillful,2 2086 | skimpy,-1 2087 | skippable,-3 2088 | skittish,-1 2089 | sky-high,-1 2090 | slack,-2 2091 | slack-jawed,-1 2092 | slanderous,-3 2093 | slapstick,-1 2094 | slavish,-3 2095 | sleazy,-3 2096 | sleek,3 2097 | sleepless,-3 2098 | slender,1 2099 | slick,3 2100 | slightly-predictable,-1 2101 | slightly-skewed,-1 2102 | slim,1 2103 | slimy,-3 2104 | slippery,-1 2105 | sloppy,-3 2106 | slothful,-3 2107 | slow-moving,-1 2108 | sluggish,-2 2109 | slumpy,-1 2110 | sluttish,-2 2111 | smallish,-1 2112 | small-town,-1 2113 | smashed,-2 2114 | smashed-up,-2 2115 | smooth,1 2116 | smoother,2 2117 | smooth-running,3 2118 | smug,-2 2119 | smutty,-2 2120 | snappy,2 2121 | snazzy,3 2122 | sneaky,-1 2123 | snot-crusted,-5 2124 | snot-nosed,-3 2125 | snotty-nosed,-4 2126 | sobering,-2 2127 | so-called,-1 2128 | social,1 2129 | sociopathic,-2 2130 | soft-porn,-3 2131 | softy,-1 2132 | soggy,-2 2133 | solemn,1 2134 | solid,1 2135 | somber,-1 2136 | sombre,-1 2137 | soothing,1 2138 | sophisticated,3 2139 | soporific,-1 2140 | sordid,-3 2141 | sore,-2 2142 | so-so,-1 2143 | soulful,1 2144 | sound,1 2145 | souped-up,2 2146 | sour,-2 2147 | space-age,1 2148 | spacey,-1 2149 | spacious,4 2150 | sparse,-1 2151 | spartan,-2 2152 | spastic,-2 2153 | special,3 2154 | specialized,3 2155 | spectacular,5 2156 | speed-on-demand,3 2157 | speedy,1 2158 | spicy,2 2159 | spirited,2 2160 | spiritless,-2 2161 | spiteful,-3 2162 | splendid,4 2163 | spoiled,-3 2164 | spongy,-2 2165 | spontaneous,1 2166 | spoon-fed,-2 2167 | sporadic,-1 2168 | sporting,2 2169 | sporty,2 2170 | spotless,4 2171 | spotty,-2 2172 | sprawling,-2 2173 | springy,1 2174 | spunky,2 2175 | spurious,-2 2176 | squat,-1 2177 | squeaky,-2 2178 | squeamish,-2 2179 | stable,1 2180 | stagnant,-3 2181 | stagy,-2 2182 | stained,-3 2183 | stainless,2 2184 | stainless-steel,2 2185 | stale,-2 2186 | stand-alone,1 2187 | standard,1 2188 | stand-offish,-2 2189 | star-crossed,-2 2190 | stark,-1 2191 | stately,2 2192 | static,-1 2193 | steady,1 2194 | steep,-1 2195 | stellar,4 2196 | stereotyped,-1 2197 | stereotypical,-1 2198 | sticky,-1 2199 | stiff,-1 2200 | stillborn,-3 2201 | stilted,-1 2202 | stimulating,2 2203 | stinky,-3 2204 | stirring,2 2205 | stodgy,-1 2206 | stormy,-1 2207 | straightforward,1 2208 | straight-forward,1 2209 | straight-line,1 2210 | strained,-2 2211 | strange,-2 2212 | strangely-shaped,-2 2213 | strategic,2 2214 | streamlined,4 2215 | stream-lined,4 2216 | street-smart,2 2217 | street-wise,2 2218 | strenous,-2 2219 | stressed-out,-4 2220 | stricken,-3 2221 | strict,-2 2222 | striking,1 2223 | struggling,-2 2224 | stubborn,-3 2225 | stubby,-2 2226 | stuck-on,-3 2227 | studious,2 2228 | stuffy,-3 2229 | stunning,4 2230 | stunted,-1 2231 | stupendous,5 2232 | stupid,-4 2233 | stupid-funny,3 2234 | sturdy,2 2235 | style-fest,1 2236 | stylish,4 2237 | stylistic,3 2238 | suave,2 2239 | sub-average,-2 2240 | sublime,5 2241 | sub-par,-2 2242 | substandard,-3 2243 | substantial,1 2244 | substantive,1 2245 | subtle,1 2246 | subversive,-3 2247 | successful,3 2248 | sufficient,1 2249 | suitable,1 2250 | sullen,-2 2251 | sultry,1 2252 | sumptuous,3 2253 | sumptuous-looking,2 2254 | sunny,3 2255 | superb,4 2256 | superdrive,3 2257 | superficial,-1 2258 | superior,4 2259 | super-luxury,5 2260 | super-violent,-3 2261 | supportive,1 2262 | supreme,4 2263 | surly,-2 2264 | surreal,-1 2265 | susceptible,-2 2266 | suspenseful,2 2267 | suspensful,1 2268 | suspicious,-2 2269 | sweet,3 2270 | swell,2 2271 | sweltering,-2 2272 | swift,1 2273 | swivel,2 2274 | sympathetic,2 2275 | symphonic,3 2276 | synchronized,3 2277 | synthetic,-1 2278 | tabloid,-4 2279 | tacked-on,-1 2280 | tacky,-3 2281 | tainted,-3 2282 | talented,2 2283 | talent-impaired,-5 2284 | talky,-1 2285 | tall,1 2286 | tame,-1 2287 | tan,1 2288 | tangible,1 2289 | tasteful,1 2290 | tasteless,-3 2291 | tasty,2 2292 | tawdry,-1 2293 | technological,1 2294 | tedious,-3 2295 | teeny,-1 2296 | teflon-coated,3 2297 | temperamental,-2 2298 | temperate,1 2299 | tempermental,-2 2300 | tempting,1 2301 | tenacious,3 2302 | tender,3 2303 | tense,-2 2304 | tepid,-2 2305 | terminal,-3 2306 | terrible,-5 2307 | terrific,5 2308 | terrifying,-3 2309 | terse,-1 2310 | thankful,1 2311 | thankless,-2 2312 | third-rate,-3 2313 | thorny,-1 2314 | thorough,2 2315 | thoughtful,2 2316 | thoughtless,-2 2317 | thrifty,1 2318 | thrilling,3 2319 | thriving,3 2320 | throaty,-1 2321 | throw-away,-1 2322 | throw-aways,-1 2323 | throw-back,-2 2324 | thugged-out,-2 2325 | thuggish,-1 2326 | tidy,1 2327 | tight,-1 2328 | tight-fitting,-1 2329 | timely,2 2330 | timid,-1 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3324 | peacefully,3 3325 | peculiarly,-1 3326 | perfunctorily,-1 3327 | persistently,-1 3328 | persuasively,1 3329 | pertinently,1 3330 | perversely,-4 3331 | pitifully,-4 3332 | plain,-1 3333 | plainly,-1 3334 | plausibly,1 3335 | playfully,2 3336 | pleasantly,3 3337 | pleasingly,4 3338 | poignantly,3 3339 | pointlessly,-4 3340 | politely,2 3341 | politically,-1 3342 | poorly,-2 3343 | popularly,3 3344 | positively,3 3345 | powerfully,3 3346 | preciously,1 3347 | precisely,2 3348 | predictably,-2 3349 | preferably,1 3350 | preposterously,-4 3351 | presumptuously,-1 3352 | pretentiously,-3 3353 | prettily,2 3354 | pricelessly,3 3355 | pricey,-1 3356 | pridefully,-1 3357 | primly,-1 3358 | proactively,2 3359 | problematically,-3 3360 | productively,1 3361 | professionally,2 3362 | proficiently,2 3363 | profitably,1 3364 | progressively,2 3365 | prohibitively,-3 3366 | prominently,1 3367 | promisingly,2 3368 | promptly,1 3369 | properly,1 3370 | protectively,-1 3371 | proudly,2 3372 | 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| rudely,-3 3423 | ruggedly,3 3424 | ruinously,-4 3425 | ruthlessly,-2 3426 | sadly,-2 3427 | safely,2 3428 | sappily,-2 3429 | satisfactorily,1 3430 | satisfyingly,3 3431 | savagely,-3 3432 | scarcely,-1 3433 | scathingly,-4 3434 | scenically,4 3435 | scientifically,1 3436 | scrumptiously,5 3437 | scrupulously,1 3438 | seamlessly,3 3439 | securely,1 3440 | seductively,1 3441 | selfishly,-3 3442 | senselessly,-3 3443 | sensitively,1 3444 | sentimentally,2 3445 | serenely,1 3446 | severely,-1 3447 | shabbily,-2 3448 | shakily,-2 3449 | shamefully,-3 3450 | shamelessly,-3 3451 | sharply,-1 3452 | sheepishly,-2 3453 | shockingly,-1 3454 | shoddily,-3 3455 | short,-1 3456 | shrewdly,1 3457 | shrilly,-3 3458 | sickeningly,-5 3459 | silently,1 3460 | simplistically,-1 3461 | sinfully,-3 3462 | sketchily,-2 3463 | skilfully,2 3464 | skillfully,2 3465 | slavishly,-3 3466 | slickly,-1 3467 | sloppily,-2 3468 | slow,-1 3469 | slowly,-1 3470 | sluggishly,-2 3471 | sly,-1 3472 | slyly,-1 3473 | 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usefully,1 3617 | uselessly,-4 3618 | usual,1 3619 | vacuously,-2 3620 | vaguely,-2 3621 | vainly,-2 3622 | valiantly,3 3623 | validly,1 3624 | viciously,-5 3625 | vigorously,2 3626 | violently,-2 3627 | virtuously,3 3628 | vitally,1 3629 | vividly,3 3630 | warily,-1 3631 | warmly,1 3632 | weakly,-2 3633 | wearily,-1 3634 | weirdly,-1 3635 | well,1 3636 | whimsically,1 3637 | wickedly,-5 3638 | willingly,1 3639 | wisely,3 3640 | wistfully,-1 3641 | wittily,3 3642 | woefully,-4 3643 | wonderfully,5 3644 | wondrously,5 3645 | woodenly,-2 3646 | worthily,4 3647 | wretchedly,-5 3648 | write-off,-4 3649 | wrong,-2 3650 | wrongfully,-2 3651 | wrongly,-2 3652 | wryly,1 3653 | (attention)_to_detail,2 3654 | (bang)_for_PSP$_buck,2 3655 | (change)_of_pace,1 3656 | (crack)_in,-2 3657 | (peak)_NN,1 3658 | abandon,-1 3659 | abandonment,-2 3660 | aberration,-2 3661 | abhorrence,-4 3662 | ability,1 3663 | abomination,-5 3664 | abrasion,-2 3665 | absurdity,-2 3666 | absurdness,-2 3667 | abundance,2 3668 | abuser,-1 3669 | acceptance,1 3670 | accident,-1 3671 | accolade,2 3672 | accommodation,-1 3673 | accomplishment,3 3674 | accusation,-2 3675 | achievement,3 3676 | acridness,-2 3677 | acrimony,-2 3678 | acumen,3 3679 | adaptability,1 3680 | admiration,3 3681 | advancement,2 3682 | advantage,2 3683 | adventure,2 3684 | affection,3 3685 | affirmation,2 3686 | affliction,-2 3687 | affront,-3 3688 | aggravation,-3 3689 | aggression,-3 3690 | agony,-4 3691 | alienation,-1 3692 | allegation,-1 3693 | allure,3 3694 | aloofness,-1 3695 | amateur,-3 3696 | ambiguity,-1 3697 | amiability,1 3698 | amicability,1 3699 | amusement,1 3700 | anarchy,-3 3701 | angel,3 3702 | angst,-1 3703 | anguish,-4 3704 | animosity,-3 3705 | annihilation,-4 3706 | annoyance,-2 3707 | anomaly,-1 3708 | anticlimax,-2 3709 | antipathy,-2 3710 | anxiety,-1 3711 | apathy,-2 3712 | apocalypse,-3 3713 | appreciation,2 3714 | apprehension,-1 3715 | aptitude,2 3716 | argument,-1 3717 | arrogance,-3 3718 | artist,1 3719 | aspersion,-2 3720 | aspiration,1 3721 | assassination,-1 3722 | asset,3 3723 | asshole,-3 3724 | assistance,1 3725 | atrocity,-4 3726 | attempt,-1 3727 | attune,1 3728 | audacity,-2 3729 | augment,1 3730 | authenticity,2 3731 | aversion,-2 3732 | avoidance,-1 3733 | awesomeness,3 3734 | awfulness,-3 3735 | awkwardness,-2 3736 | backwardness,-3 3737 | bafflement,-3 3738 | balance,1 3739 | banality,-3 3740 | bandit,-1 3741 | bandwagon,-2 3742 | bane,-3 3743 | barbarian,-1 3744 | barbarity,-3 3745 | bargain,2 3746 | barrier,-2 3747 | bastard,-3 3748 | battering,-2 3749 | beacon,1 3750 | beast,-1 3751 | beauty,4 3752 | beggar,-2 3753 | belligerence,-3 3754 | benefit,3 3755 | benevolence,1 3756 | best-seller,2 3757 | betrayal,-4 3758 | bewilderment,-3 3759 | bible-thumper,-1 3760 | bickering,-2 3761 | bimbo,-2 3762 | bitterness,-2 3763 | blabbermouth,-1 3764 | blackmail,-3 3765 | blame,-2 3766 | bleakness,-2 3767 | blemish,-1 3768 | blessing,2 3769 | bliss,4 3770 | blockbuster,2 3771 | bloodshed,-2 3772 | bluff,-1 3773 | boldness,3 3774 | bombardment,-1 3775 | bondage,-1 3776 | bonus,2 3777 | boom,2 3778 | boredom,-3 3779 | bounty,3 3780 | bout,-1 3781 | brat,-2 3782 | bravado,-1 3783 | bravery,3 3784 | brawl,-2 3785 | brazenness,-1 3786 | breakthrough,2 3787 | breakup,-1 3788 | brightness,3 3789 | brilliance,4 3790 | brood,-1 3791 | brotherhood,1 3792 | brutality,-3 3793 | brute,-2 3794 | buddy,1 3795 | bullshit,-3 3796 | bully,-1 3797 | bum,-1 3798 | bummer,-2 3799 | bump,-1 3800 | burden,-3 3801 | bureaucracy,-1 3802 | butchery,-3 3803 | buzz,1 3804 | calamity,-4 3805 | cancellation,-1 3806 | cancer,-3 3807 | candor,2 3808 | cannibal,-4 3809 | capability,2 3810 | capriciousness,-1 3811 | captive,1 3812 | carelessness,-2 3813 | caricature,-2 3814 | carnage,-2 3815 | casualty,-2 3816 | cataclysm,-4 3817 | catastrophe,-5 3818 | catch,-1 3819 | chagrin,-3 3820 | champion,3 3821 | chaos,-2 3822 | charisma,3 3823 | charity,2 3824 | charm,3 3825 | cheater,-2 3826 | cheek,-2 3827 | cheer,3 3828 | cheerfulness,1 3829 | chivalry,2 3830 | chore,-3 3831 | chum,1 3832 | cinch,2 3833 | civility,2 3834 | clamor,-2 3835 | clarity,1 3836 | classic,4 3837 | claustrophobia,-1 3838 | cleanliness,1 3839 | clearness,1 3840 | clich?,-2 3841 | cliche,-2 3842 | clique,-2 3843 | clone,-1 3844 | closemindedness,-3 3845 | closeness,1 3846 | clout,1 3847 | clumsiness,-2 3848 | clutches,-1 3849 | cockiness,-2 3850 | coercion,-2 3851 | coherence,1 3852 | cohesion,2 3853 | collaboration,2 3854 | collapose,-2 3855 | collision,-1 3856 | collusion,-2 3857 | comedy,1 3858 | commemoration,2 3859 | commendation,3 3860 | commiseration,-2 3861 | commitment,2 3862 | commotion,-2 3863 | community,1 3864 | companion,1 3865 | companionship,1 3866 | compassion,2 3867 | compensation,1 3868 | competence,2 3869 | complaint,-2 3870 | complexity,-1 3871 | complication,-2 3872 | composure,1 3873 | compulsion,-2 3874 | conceit,-2 3875 | concern,-1 3876 | concoction,-2 3877 | condemnation,-3 3878 | condescension,-2 3879 | confidence,2 3880 | conformity,-1 3881 | confrontation,-1 3882 | confusion,-2 3883 | congestion,-2 3884 | congratulation,2 3885 | conquest,2 3886 | conscience,2 3887 | consent,1 3888 | consequence,-2 3889 | consistency,2 3890 | conspiracy,-2 3891 | constancy,1 3892 | consternation,-3 3893 | contamination,-2 3894 | contempt,-3 3895 | content,1 3896 | contentment,2 3897 | continuity,2 3898 | contradiction,-1 3899 | contribution,2 3900 | contrivance,-3 3901 | controversy,-2 3902 | convenience,1 3903 | convention,-1 3904 | conviction,1 3905 | cooperation,2 3906 | coordination,2 3907 | cornucopia,3 3908 | correction,1 3909 | corrosion,-3 3910 | corruption,-3 3911 | cost,-1 3912 | costliness,-2 3913 | courage,2 3914 | courageousness,2 3915 | courtesy,1 3916 | coward,-3 3917 | crack,-1 3918 | crap,-4 3919 | crappiness,-4 3920 | crash,-2 3921 | craziness,-1 3922 | creativity,3 3923 | credential,1 3924 | credibility,2 3925 | credulity,-1 3926 | creepiness,-1 3927 | crime,-2 3928 | crisis,-3 3929 | critic,-2 3930 | criticism,-1 3931 | critique,-2 3932 | cronie,-2 3933 | crony,-2 3934 | crook,-1 3935 | crotch,-1 3936 | cruelty,-2 3937 | culmination,4 3938 | culprit,-2 3939 | culture,1 3940 | curmudgeon,-2 3941 | cynicism,-3 3942 | danger,-2 3943 | dangerousness,-1 3944 | dark_(age),-2 3945 | darkness,-1 3946 | deadlock,-2 3947 | deadweight,-2 3948 | dearth,-1 3949 | death,-1 3950 | debacle,-4 3951 | debauchery,-3 3952 | decadence,-2 3953 | deceit,-2 3954 | deceiver,-2 3955 | decency,2 3956 | deception,-2 3957 | dedication,3 3958 | defamation,-2 3959 | defect,-2 3960 | deficiency,-2 3961 | deficit,-1 3962 | degeneration,-2 3963 | degradation,-2 3964 | dehumanization,-3 3965 | dejection,-2 3966 | delightfulness,3 3967 | delinquency,-2 3968 | deluge,-1 3969 | delusion,-2 3970 | dementia,-3 3971 | demon,-3 3972 | denial,-1 3973 | dent,-1 3974 | denunciation,-3 3975 | dependability,2 3976 | depravity,-3 3977 | depression,-2 3978 | depth,2 3979 | derision,-3 3980 | derivative,-2 3981 | desolation,-3 3982 | desperation,-3 3983 | despondency,-3 3984 | despot,-2 3985 | despotism,-1 3986 | destabilisation,-1 3987 | destitution,-4 3988 | destroyer,-2 3989 | destruction,-2 3990 | detachment,-1 3991 | deterioration,-3 3992 | determination,1 3993 | detour,-1 3994 | detraction,-2 3995 | detriment,-2 3996 | devastation,-4 3997 | devestation,-3 3998 | deviant,-2 3999 | deviation,-1 4000 | devil,-1 4001 | deviousness,-2 4002 | devotion,3 4003 | dexterity,2 4004 | diatribe,-3 4005 | dictator,-3 4006 | difficulty,-1 4007 | dignity,2 4008 | dilemma,-1 4009 | diligence,1 4010 | din,-1 4011 | direness,-3 4012 | dirt,-1 4013 | disaccord,-1 4014 | disadvantage,-2 4015 | disadvantageous,-1 4016 | disagreement,-1 4017 | disappointment,-3 4018 | disapproval,-2 4019 | disarray,-3 4020 | disaster,-4 4021 | disbelief,-1 4022 | discoloration,-1 4023 | discomfort,-1 4024 | discord,-1 4025 | discount,1 4026 | discrimination,-2 4027 | disdain,-3 4028 | disease,-1 4029 | dishonesty,-2 4030 | disillusionment,-2 4031 | disinterest,-1 4032 | dismalness,-3 4033 | dismay,-3 4034 | disobedience,-1 4035 | disorder,-1 4036 | disorganization,-2 4037 | displeasure,-2 4038 | disregard,-1 4039 | disrepute,-2 4040 | disrespectablity,-1 4041 | disrespectfulness,-1 4042 | disruption,-2 4043 | dissatisfaction,-2 4044 | dissent,-1 4045 | dissention,-1 4046 | disservice,-2 4047 | dissolution,-1 4048 | distaste,-2 4049 | distinction,2 4050 | distortion,-2 4051 | distraction,-1 4052 | distrust,-2 4053 | disturbance,-1 4054 | disunity,-1 4055 | diversity,1 4056 | divinity,3 4057 | divisiveness,-2 4058 | dogma,-2 4059 | doldrum,-2 4060 | doldrums,-2 4061 | dominance,2 4062 | domination,-1 4063 | donation,1 4064 | doubt,-1 4065 | downer,-2 4066 | downfall,-3 4067 | downfallen,-3 4068 | downside,-1 4069 | drawback,-1 4070 | dreadfulness,-4 4071 | dream,1 4072 | dreariness,-2 4073 | dreck,-4 4074 | drudgery,-2 4075 | dullness,-2 4076 | dunce,-2 4077 | durability,2 4078 | duty,-1 4079 | dysfunction,-2 4080 | eagerness,1 4081 | earnestness,2 4082 | ease,1 4083 | eccentricity,-1 4084 | ecstasy,4 4085 | effectiveness,2 4086 | efficacy,2 4087 | egomania,-3 4088 | egotism,-1 4089 | elaboration,1 4090 | elan,2 4091 | elation,3 4092 | elegance,2 4093 | elimination,-2 4094 | eloquence,2 4095 | embarassment,-2 4096 | embarrasment,-3 4097 | embarrassment,-2 4098 | emergency,-1 4099 | eminence,3 4100 | empathy,2 4101 | empowerment,1 4102 | emptiness,-1 4103 | enchantment,3 4104 | encouragement,2 4105 | encroachment,-2 4106 | endorsement,2 4107 | enemy,-1 4108 | energy,1 4109 | enhancement,2 4110 | enjoyment,3 4111 | enlightenment,1 4112 | ennui,-2 4113 | enrichment,2 4114 | entanglement,-1 4115 | entertainment,2 4116 | enthusiasm,2 4117 | enviousness,-1 4118 | epidemic,-3 4119 | epithet,-2 4120 | equality,2 4121 | erosion,-2 4122 | error,-2 4123 | ethic,1 4124 | etiquette,1 4125 | euphoria,4 4126 | evasion,-1 4127 | exaggeration,-2 4128 | exasperation,-3 4129 | excellence,4 4130 | excess,-2 4131 | excitedness,1 4132 | excitement,2 4133 | exclusion,-1 4134 | excuse,-1 4135 | exhaustion,-1 4136 | exhilaration,4 4137 | expense,-2 4138 | experise,2 4139 | expert,2 4140 | exploitation,-3 4141 | extermination,-3 4142 | extortion,-3 4143 | extravagance,-1 4144 | extreme,-1 4145 | extremism,-1 4146 | exuberance,3 4147 | exultation,3 4148 | fabrication,-3 4149 | failing,-2 4150 | failure,-3 4151 | fairness,2 4152 | faith,2 4153 | faithfulness,3 4154 | fake,-2 4155 | fallacy,-1 4156 | fallout,-1 4157 | falsehood,-2 4158 | fame,1 4159 | familiarity,1 4160 | famine,-2 4161 | fan,2 4162 | fanatic,-2 4163 | fanaticism,-2 4164 | fantasy,1 4165 | farce,-2 4166 | fascination,3 4167 | fascist,-5 4168 | fate,-1 4169 | fear,-2 4170 | feast,2 4171 | feat,2 4172 | feature,2 4173 | feint,-1 4174 | felicity,2 4175 | fellowship,2 4176 | ferocity,-1 4177 | fervor,2 4178 | festivity,1 4179 | fiasco,-5 4180 | fidelity,2 4181 | fiend,-3 4182 | filth,-3 4183 | firmness,1 4184 | fitness,2 4185 | flair,2 4186 | flattery,-1 4187 | flaw,-3 4188 | flick,-2 4189 | flimsiness,-1 4190 | flourish,1 4191 | fluff,-2 4192 | fondness,1 4193 | foolishness,-2 4194 | foresight,2 4195 | forgiveness,1 4196 | formality,-1 4197 | fortitude,1 4198 | fortune,2 4199 | fraud,-3 4200 | freak,-2 4201 | freedom,2 4202 | frenzy,-1 4203 | freshness,3 4204 | fretful,-1 4205 | friend,2 4206 | friendliness,2 4207 | friendship,2 4208 | fruition,2 4209 | frustration,-2 4210 | fulfillment,3 4211 | fury,-1 4212 | fuss,-1 4213 | futility,-2 4214 | gaffe,-1 4215 | gag,1 4216 | gaiety,3 4217 | gall,-3 4218 | gallantry,2 4219 | garbage,-2 4220 | gawker,-2 4221 | gem,2 4222 | generalization,-1 4223 | generosity,2 4224 | genius,4 4225 | germ,-1 4226 | ghetto,-2 4227 | gift,2 4228 | gimmick,-1 4229 | gladness,1 4230 | glamour,2 4231 | glee,3 4232 | glitch,-1 4233 | gloom,-2 4234 | glory,3 4235 | glut,-2 4236 | goddess,2 4237 | goodness,2 4238 | goodwill,2 4239 | grace,3 4240 | graciousness,2 4241 | gratification,1 4242 | gratitude,2 4243 | greatness,3 4244 | greed,-3 4245 | grief,-1 4246 | grievance,-3 4247 | grime,-3 4248 | groan,-2 4249 | grouch,-1 4250 | grudge,-2 4251 | guarantee,2 4252 | guardian,1 4253 | guilt,-3 4254 | guise,-2 4255 | gulf,-1 4256 | gumption,3 4257 | gunk,-2 4258 | gusto,3 4259 | hack,-3 4260 | hag,-2 4261 | hallucination,-1 4262 | handicap,-2 4263 | happiness,2 4264 | harassment,-2 4265 | hardship,-1 4266 | harmony,2 4267 | harpy,-3 4268 | harshness,-1 4269 | hassle,-1 4270 | hatefulness,-3 4271 | hatred,-4 4272 | haughtiness,-1 4273 | haven,2 4274 | havoc,-3 4275 | hazard,-1 4276 | haze,-1 4277 | haziness,-2 4278 | headache,-2 4279 | health,2 4280 | heart,1 4281 | heaven,3 4282 | hegemony,-3 4283 | hell,-3 4284 | helper,1 4285 | helpfulness,1 4286 | helplessness,-2 4287 | heresy,-2 4288 | heretic,-3 4289 | hero,2 4290 | heroine,2 4291 | heroism,3 4292 | hideousness,-4 4293 | hilariousness,3 4294 | hilarity,3 4295 | hindrance,-2 4296 | hit,2 4297 | homage,1 4298 | honesty,2 4299 | honor,3 4300 | honour,3 4301 | hooey,-3 4302 | hope,1 4303 | horde,-2 4304 | hostility,-2 4305 | hothead,-1 4306 | hubris,-2 4307 | huckster,-1 4308 | humanity,3 4309 | humiliation,-3 4310 | humility,1 4311 | humor,2 4312 | humour,1 4313 | hurtle,-1 4314 | hustler,-2 4315 | hype,-2 4316 | hypocrisy,-3 4317 | hypocrite,-3 4318 | hysteria,-2 4319 | hysteric,-3 4320 | idealism,2 4321 | idiot,-3 4322 | idleness,-1 4323 | ignorance,-3 4324 | illegality,-1 4325 | illness,-1 4326 | illogic,-1 4327 | ill-treatment,-1 4328 | ill-usage,-1 4329 | imagination,2 4330 | immorality,-3 4331 | impact,1 4332 | impartiality,1 4333 | impasse,-1 4334 | impatience,-2 4335 | impediment,-2 4336 | imperfection,-1 4337 | impetus,1 4338 | impiety,-2 4339 | importance,2 4340 | imposition,-1 4341 | imposter,-2 4342 | impression,1 4343 | imprisonment,-1 4344 | impropriety,-1 4345 | improvement,2 4346 | imprudence,-1 4347 | impudence,-3 4348 | impunity,-2 4349 | impurity,-2 4350 | inaccuracy,-2 4351 | inadequacy,-3 4352 | inaptitude,-2 4353 | incident,-1 4354 | incoherence,-3 4355 | incompatibility,-2 4356 | incompatible,-2 4357 | incompetence,-3 4358 | inconsistency,-2 4359 | inconvenience,-1 4360 | indecency,-2 4361 | independence,1 4362 | indictment,-2 4363 | indifference,-1 4364 | indignation,-3 4365 | indignity,-2 4366 | indispensabilty,1 4367 | indoctrination,-3 4368 | indulgence,-1 4369 | ineffectiveness,-2 4370 | ineffectualness,-1 4371 | inefficacy,-1 4372 | inefficiency,-2 4373 | inelegance,-1 4374 | ineptitude,-2 4375 | inequality,-1 4376 | inequities,-2 4377 | inexperience,-1 4378 | infallibility,-1 4379 | infamy,-3 4380 | infection,-3 4381 | inferiority,-2 4382 | infidel,-3 4383 | infiltration,-1 4384 | inflation,-1 4385 | infraction,-1 4386 | infringement,-1 4387 | ingenuity,3 4388 | ingrate,-2 4389 | ingratitude,-2 4390 | inhibition,-1 4391 | inhospitality,-2 4392 | inhumanity,-3 4393 | iniquity,-2 4394 | injury,-2 4395 | injustice,-3 4396 | innocence,2 4397 | innovation,2 4398 | insanity,-3 4399 | insecurity,-2 4400 | insensitivity,-1 4401 | insight,3 4402 | insignificance,-2 4403 | insincerity,-2 4404 | insolence,-2 4405 | inspiration,3 4406 | instability,-1 4407 | insufficiency,-1 4408 | integrity,2 4409 | intellect,1 4410 | intelligence,3 4411 | intensity,2 4412 | interference,-1 4413 | interruption,-1 4414 | intimacy,1 4415 | intimidation,-1 4416 | intolerance,-3 4417 | intrusion,-1 4418 | inventiveness,2 4419 | invidiousness,-2 4420 | ire,-2 4421 | irony,-1 4422 | irrationality,-2 4423 | irregularity,-1 4424 | irrelevance,-1 4425 | irritant,-2 4426 | irritation,-1 4427 | isolation,-1 4428 | issue,-1 4429 | jargon,-1 4430 | jealousy,-1 4431 | jeopardy,-1 4432 | jewel,2 4433 | joke,1 4434 | jolt,-1 4435 | joy,3 4436 | jubilation,4 4437 | jubilee,2 4438 | junk,-3 4439 | justice,1 4440 | killer,-3 4441 | kindness,2 4442 | knell,-3 4443 | knock-off,-2 4444 | kudos,2 4445 | lackey,-1 4446 | lag,-1 4447 | lapse,-1 4448 | lard,-2 4449 | laughingstock,-3 4450 | laughter,1 4451 | lawlessness,-1 4452 | laziness,-2 4453 | lechery,-3 4454 | leech,-3 4455 | legitmacy,1 4456 | letdown,-3 4457 | lewdness,-2 4458 | liability,-3 4459 | liar,-2 4460 | licentiousness,-2 4461 | limitation,-2 4462 | liquidation,-1 4463 | loathing,-4 4464 | logic,1 4465 | loneliness,-2 4466 | loser,-1 4467 | loss,-2 4468 | loveliness,3 4469 | lover,2 4470 | loyalty,2 4471 | luck,1 4472 | luckiness,1 4473 | lull,-2 4474 | lunatic,-3 4475 | luster,1 4476 | luxury,2 4477 | lying,-2 4478 | lyricism,2 4479 | madman,-2 4480 | madness,-2 4481 | maggot,-3 4482 | magic,1 4483 | magnificence,4 4484 | majesty,3 4485 | maladjustment,-1 4486 | malady,-2 4487 | malaise,-1 4488 | malevolence,-3 4489 | malice,-2 4490 | maliciousness,-3 4491 | maltreatment,-2 4492 | maniac,-3 4493 | manipulation,-2 4494 | mantra,-1 4495 | masochism,-2 4496 | masterpiece,5 4497 | mastery,4 4498 | maturity,1 4499 | meanness,-2 4500 | mediocrity,-2 4501 | meditation,1 4502 | melancholy,-2 4503 | melodrama,-3 4504 | mercy,2 4505 | merit,3 4506 | merriment,2 4507 | milestone,3 4508 | miracle,2 4509 | mirth,1 4510 | misadventures,-2 4511 | misbehavior,-1 4512 | miscalculation,-1 4513 | mischief,-1 4514 | misconception,-1 4515 | miscreant,-2 4516 | misdirection,-1 4517 | misery,-4 4518 | misfit,-1 4519 | misfortune,-2 4520 | misgiving,-1 4521 | mish_(mash),-2 4522 | mishap,-1 4523 | mishmash,-2 4524 | mismanagement,-2 4525 | misogynist,-3 4526 | misogyny,-2 4527 | missteps,1 4528 | mistake,-2 4529 | misunderstanding,-1 4530 | mockery,-3 4531 | moderation,1 4532 | modernity,1 4533 | modesty,1 4534 | modicum,-3 4535 | mold,-2 4536 | molestation,-3 4537 | monotony,-3 4538 | monster,-2 4539 | monstrosity,-5 4540 | moral,2 4541 | morale,1 4542 | morality,2 4543 | moron,-3 4544 | motivation,1 4545 | muddle,-2 4546 | multitude,1 4547 | mumbo-jumbo,-2 4548 | mundane,-3 4549 | mutant,-2 4550 | nastiness,-3 4551 | negation,-2 4552 | negative,-2 4553 | negativity,-1 4554 | negligence,-2 4555 | nervousness,-1 4556 | nightmare,-3 4557 | no_frills,-1 4558 | no_point,-3 4559 | no_way,-4 4560 | nobility,3 4561 | noise,-1 4562 | nonsense,-3 4563 | not_$PRP_(cup)_of_tea,-1 4564 | notoriety,2 4565 | nourishment,1 4566 | novelty,1 4567 | novice,-1 4568 | nuances,1 4569 | nuisance,-2 4570 | nullification,-1 4571 | nutrient,1 4572 | obedience,1 4573 | objection,-1 4574 | obscenity,-3 4575 | obscurity,-1 4576 | obsession,-2 4577 | obstacle,-3 4578 | obstruction,-2 4579 | oddity,-1 4580 | offense,-1 4581 | offensiveness,-2 4582 | omission,-1 4583 | onslaught,-2 4584 | opportunity,1 4585 | opposition,-2 4586 | oppression,-2 4587 | oppressiveness,-2 4588 | optimism,1 4589 | opulence,-1 4590 | ordeal,-3 4591 | originality,3 4592 | outbreak,-2 4593 | outcast,-1 4594 | outcry,-2 4595 | outrageousness,-3 4596 | overkill,-1 4597 | over-reliance,-1 4598 | oversight,-1 4599 | oversimplification,-1 4600 | overuse,-1 4601 | 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posterity,1 4654 | potency,3 4655 | poverty,-2 4656 | power,1 4657 | precaution,1 4658 | precedent,1 4659 | predator,-1 4660 | predicament,-1 4661 | predictability,-1 4662 | prejudice,-2 4663 | preoccupation,-1 4664 | pressure,-1 4665 | prestige,2 4666 | presumption,-1 4667 | pretense,-2 4668 | pretension,-2 4669 | pretention,-2 4670 | pride,2 4671 | pro,1 4672 | problem,-2 4673 | procrastination,-1 4674 | prodigy,2 4675 | productivity,1 4676 | profoundness,3 4677 | prohibition,-1 4678 | prominence,2 4679 | promise,2 4680 | propaganda,-3 4681 | prosecution,-2 4682 | prosperity,2 4683 | protagonist,1 4684 | protection,1 4685 | provocation,2 4686 | prowess,3 4687 | prudence,2 4688 | psycho,-3 4689 | psychosis,-3 4690 | purification,1 4691 | purity,2 4692 | pussy,-3 4693 | puzzlement,-1 4694 | quagmire,-3 4695 | qualm,-2 4696 | quandary,-1 4697 | quarrel,-1 4698 | quitter,-2 4699 | radiance,3 4700 | rambing,-1 4701 | rancor,-2 4702 | rape,-4 4703 | rapport,2 4704 | rapture,3 4705 | 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revulsion,-4 4755 | riches,1 4756 | richness,3 4757 | rift,-1 4758 | righteousness,2 4759 | rigidity,-1 4760 | rip-off,-3 4761 | robber,-2 4762 | robbery,-2 4763 | rogue,-1 4764 | romance,2 4765 | roughness,-2 4766 | rouse,-1 4767 | rowdiness,-1 4768 | rubbish,-3 4769 | rudeness,-2 4770 | ruffian,-2 4771 | rumor,-1 4772 | ruthlessness,-4 4773 | sadness,-1 4774 | safety,2 4775 | sagacity,2 4776 | saint,3 4777 | salutation,1 4778 | salvation,1 4779 | sanctity,1 4780 | sanctuary,2 4781 | sanity,1 4782 | sarcasm,-1 4783 | satisfaction,2 4784 | savagery,-3 4785 | scam,-3 4786 | scam-artist,-1 4787 | scandal,-3 4788 | scapegoat,-2 4789 | scar,-2 4790 | scarcity,-1 4791 | scheme,-1 4792 | schlock,-3 4793 | scorn,-3 4794 | scoundrel,-3 4795 | scourge,-3 4796 | scream,-2 4797 | scruples,2 4798 | scrutiny,-1 4799 | scuff,-1 4800 | scuffle,-1 4801 | scum,-3 4802 | secrecy,-1 4803 | security,2 4804 | segregation,-2 4805 | selfishness,-3 4806 | self-respect,3 4807 | semblance,1 4808 | sensation,2 4809 | sensitivity,1 4810 | sentimentality,-1 4811 | serenity,3 4812 | seriousness,1 4813 | servitude,-2 4814 | severity,-3 4815 | shadow,-1 4816 | sham,-3 4817 | shamefulness,-2 4818 | shamelessness,-3 4819 | shark,-1 4820 | shelter,1 4821 | shenanigan,-1 4822 | shock,-2 4823 | shortage,-2 4824 | shortcoming,-2 4825 | shortfall,-1 4826 | shrew,-1 4827 | shrewdness,2 4828 | shriek,-2 4829 | shyness,-1 4830 | sickness,-2 4831 | significance,2 4832 | silliness,2 4833 | simplicity,2 4834 | sin,-2 4835 | sincerity,3 4836 | skill,2 4837 | skirmish,-1 4838 | slime,-3 4839 | slop,-1 4840 | sloth,-2 4841 | sluggishness,-2 4842 | slump,-2 4843 | smash,2 4844 | snub,-2 4845 | softness,2 4846 | solace,1 4847 | solution,2 4848 | sorrow,-2 4849 | soundness,1 4850 | spawn,-3 4851 | spectacle,-2 4852 | spell,1 4853 | spinster,-2 4854 | spirituality,1 4855 | spite,-3 4856 | splendor,3 4857 | spontaneity,1 4858 | stability,1 4859 | stalemate,-1 4860 | standout,2 4861 | stand-out,2 4862 | starvation,-3 4863 | stature,2 4864 | staunchness,1 4865 | steadfastness,1 4866 | steadiness,1 4867 | stench,-3 4868 | stereotype,-2 4869 | stigma,-3 4870 | stimulation,1 4871 | stinker,-3 4872 | straggler,-1 4873 | strangeness,-1 4874 | strength,2 4875 | stress,-1 4876 | strides,2 4877 | strife,-2 4878 | stubborness,-2 4879 | stubbornness,-1 4880 | stud,3 4881 | stupidity,-3 4882 | stupor,-3 4883 | subjection,-2 4884 | subjugation,-3 4885 | subservience,-2 4886 | substance,1 4887 | subversion,-2 4888 | success,3 4889 | sucker,-3 4890 | suckiness,-3 4891 | suffering,-2 4892 | superficiality,-3 4893 | superiority,2 4894 | superstition,-2 4895 | suppression,-1 4896 | surge,2 4897 | suspicion,-2 4898 | sweetheart,2 4899 | sweetness,3 4900 | swiftness,2 4901 | swill,-2 4902 | sympathy,2 4903 | symptom,-1 4904 | synthesis,1 4905 | taboo,-1 4906 | tact,2 4907 | talent,3 4908 | tantrum,-3 4909 | taste,2 4910 | temper,-1 4911 | temperance,1 4912 | tempest,-1 4913 | temptation,-2 4914 | tenacity,2 4915 | tenderness,2 4916 | tension,-2 4917 | terribleness,-4 4918 | terror,-4 4919 | terrorism,-4 4920 | theft,-2 4921 | thief,-2 4922 | thirst,-1 4923 | thoughtfulness,3 4924 | thoughtlessness,-2 4925 | threat,-2 4926 | thrift,1 4927 | thud,-1 4928 | time-waster,-2 4929 | timidity,-2 4930 | timidness,-1 4931 | tirade,-3 4932 | tolerance,2 4933 | toleration,1 4934 | torrent,-1 4935 | toughness,1 4936 | tour-de-force,4 4937 | tragedy,-3 4938 | traitor,-3 4939 | tramp,-1 4940 | tranquility,2 4941 | transgression,-2 4942 | trap,-2 4943 | trash,-3 4944 | trauma,-2 4945 | travesty,-4 4946 | treachery,-4 4947 | treason,-4 4948 | treat,2 4949 | trepidation,-1 4950 | tribute,2 4951 | trickery,-2 4952 | trophy,1 4953 | trouble,-2 4954 | troublemaker,-2 4955 | trustworthiness,3 4956 | truth,1 4957 | turmoil,-1 4958 | tyranny,-3 4959 | tyrant,-3 4960 | ugliness,-2 4961 | ultimatum,-1 4962 | undependability,-2 4963 | understanding,1 4964 | unease,-1 4965 | uneasiness,-1 4966 | unemployment,-1 4967 | unfaithfulness,-2 4968 | unhappiness,-2 4969 | uniqueness,2 4970 | unity,2 4971 | unlawfulness,-1 4972 | unpleasantness,-2 4973 | unreliability,-2 4974 | unrest,-1 4975 | unsteadiness,-1 4976 | untruth,-1 4977 | unwillingness,-2 4978 | uproar,-2 4979 | usefulness,1 4980 | usurper,-3 4981 | vagrant,-2 4982 | vagueness,-2 4983 | validity,1 4984 | valor,3 4985 | value,3 4986 | variety,1 4987 | vastness,2 4988 | venom,-3 4989 | versatility,3 4990 | vexation,-2 4991 | viability,1 4992 | vice,-2 4993 | viciousness,-3 4994 | victim,-2 4995 | victory,2 4996 | vileness,-4 4997 | villain,-2 4998 | villian,-3 4999 | vindictiveness,-3 5000 | violation,-2 5001 | violence,-2 5002 | viper,-2 5003 | virtue,2 5004 | virulence,-2 5005 | virus,-3 5006 | visionary,3 5007 | vitality,2 5008 | void,-1 5009 | volatility,-1 5010 | volatily,-2 5011 | vulgarity,-2 5012 | wannabe,-3 5013 | war,-2 5014 | warmth,2 5015 | warning,-1 5016 | wastefulness,-2 5017 | weakness,-2 5018 | weariness,-1 5019 | weirdness,-1 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5065 | (#go#)_against,-1 5066 | (#go#)_under,-3 5067 | (#grow#)_apart,-1 5068 | (#grow#)_on_$PRP,2 5069 | (#hang#)_together,1 5070 | (#have#)_[INT]?_no_clue,-2 5071 | (#have#)_it_all,4 5072 | (#hold#)_[PRP$]_attention,2 5073 | (#hold#)_up,1 5074 | (#make#)_[INT]?_sense,1 5075 | (#run#)_out,-1 5076 | (#see#)_DT_point,1 5077 | (#stand#)_out,1 5078 | (#string#)_along,-2 5079 | (#take#)_DT_hit,-2 5080 | (#think#)_[INT]?_highly_of,3 5081 | (act)_funny,-1 5082 | (amount)_to,1 5083 | (back)_out,-1 5084 | (beat)_#PER?#_out,1 5085 | (beef)_up,2 5086 | (believe)_in,1 5087 | (bog)_down,-2 5088 | (boot)_out,-2 5089 | (bowl)_#PER?#_over,2 5090 | (branch)_out,2 5091 | (brighten)_#NP?#_up,2 5092 | (brush)_#PER?#_off,-1 5093 | (build|built)_up,1 5094 | (cash)_in-on,-2 5095 | (cast)_aside,-2 5096 | (caught)_up_in,2 5097 | (chicken)_out,-3 5098 | (choke)_#NP?#_down,-2 5099 | (coop)_up,-2 5100 | (cop)_out,-2 5101 | (crawl)_with,-1 5102 | (cut)_off,-1 5103 | (deck)_out,2 5104 | (dream)_on,-3 5105 | (drift)_apart,-1 5106 | (drive)_#PER?#_away,-2 5107 | (drive)_#PER?#_nuts,-3 5108 | (dumb)_down,-2 5109 | (follow)_through,1 5110 | (fritter)_away,-1 5111 | (fuck)_#NP?#_up,-3 5112 | (fuck)_#PER?#_over,-4 5113 | (gang)_up,-1 5114 | (gross)_#PER?#_out,-2 5115 | (hit)_it_off,2 5116 | (jazz)_#NP?#_up,2 5117 | (jerk)_#PER?#_around,-2 5118 | (juice)_#NP?#_up,1 5119 | (kick)_#PER?#_out,-1 5120 | (lag)_behind,-1 5121 | (lash)_out,-2 5122 | (let)_#PER?#_down,-2 5123 | (light)_#NP?#_up,1 5124 | (limit)_#NP?#_to,-2 5125 | (liven)_up,1 5126 | (load)_down,-1 5127 | (look)_down_on,-1 5128 | (look)_forward_to,1 5129 | (luck)_out,2 5130 | (mess)_#NP?#_up,-3 5131 | (mess)_with,-2 5132 | (object)_to,-1 5133 | (pad)_#NP?#_out,-1 5134 | (pale)_in,-2 5135 | (palm)_off,-1 5136 | (pan)_out,1 5137 | (pander)_to,-2 5138 | (pass)_#NP?#_off_as,-1 5139 | (perk)_#PER?#_up,1 5140 | (pick)_on,-1 5141 | (piss)_#PER?#_off,-3 5142 | (plan)_ahead,1 5143 | (pose)_as,-1 5144 | (profit)_from,1 5145 | (pull)_#NP?#_off,2 5146 | (put)_#PER?#_off,-2 5147 | (put)_up_with,-1 5148 | (reek)_of,-3 5149 | (resonate)_with,1 5150 | (rip)_off,-3 5151 | (roll)_over_in_PRP$_grave,-4 5152 | (saddle)_with,-1 5153 | (scrape)_by,-1 5154 | (set)_#NP?#_apart,2 5155 | (settle)_[with|for],-1 5156 | (shake)_#PER?#_up,-1 5157 | (shape)_up,1 5158 | (shell)_out,-1 5159 | (shirk)_from,-2 5160 | (show)_off,-1 5161 | (shut)_up,-2 5162 | (skimp)_on,-1 5163 | (skip)_it,-2 5164 | (slap)_on,-2 5165 | (smack)_of,-1 5166 | (smooth)_[out|over],1 5167 | (spice)_$NP?#_up,1 5168 | (stay)_away,-2 5169 | (steer)_clear,-2 5170 | (stir)_$NP?#_up,-1 5171 | (straighten)_out,1 5172 | (suck)_#PER?#_in,3 5173 | (talk)_down_to,-1 5174 | (thrive)_on,3 5175 | (touched)_by,2 5176 | (turn)_$NP?#_down,-1 5177 | (turn)_[INT]_heads,3 5178 | (turn)_against,-1 5179 | (walk)_out,-2 5180 | (wallow)_in,-2 5181 | (wear)_#NP?#_out,-1 5182 | (weasel)_out_of,-3 5183 | (weigh)_on,-2 5184 | (wimp)_out,-2 5185 | (wipe)_out,-2 5186 | [#can#]_(#do#)_better,-2 5187 | [#can#]_(#do#)_without,-2 5188 | [#can#]_(#do#)_worse,1 5189 | [#can#]_not_(put)_#NP?#_down,4 5190 | [all|everything]_that_it_was_(cracked)_up_to_be,2 5191 | abase,-2 5192 | abhor,-5 5193 | abolish,-2 5194 | absolve,1 5195 | abuse,-3 5196 | accept,1 5197 | accommodate,1 5198 | accomodate,1 5199 | accomplish,1 5200 | accost,-2 5201 | accuse,-2 5202 | acerbate,-2 5203 | ache,-1 5204 | achieve,3 5205 | admire,3 5206 | adore,4 5207 | affirm,1 5208 | afflict,-2 5209 | aggravate,-3 5210 | agitate,-2 5211 | agonize,-4 5212 | aid,2 5213 | alarm,-3 5214 | alienate,-3 5215 | allege,-2 5216 | alleviate,1 5217 | amaze,3 5218 | ambush,-2 5219 | ameliorate,2 5220 | amputate,-2 5221 | amuse,2 5222 | anger,-2 5223 | annihilate,-4 5224 | annoy,-2 5225 | antagonize,-2 5226 | anticipate,1 5227 | appal,-3 5228 | appall,-5 5229 | appease,1 5230 | applaud,2 5231 | appreciate,2 5232 | approve,2 5233 | argue,-1 5234 | aspire,1 5235 | assassinate,-2 5236 | assault,-3 5237 | assist,1 5238 | atrophy,-3 5239 | attack,-2 5240 | attain,1 5241 | attract,2 5242 | attraction,2 5243 | aunguish,-2 5244 | avert,-2 5245 | award,1 5246 | awe,4 5247 | babble,-2 5248 | badger,-2 5249 | baffle,-3 5250 | balk,-2 5251 | banish,-2 5252 | barge,-1 5253 | bash,-2 5254 | bastardize,-3 5255 | battle,-1 5256 | bear,-1 5257 | beat,-2 5258 | beautify,3 5259 | befit,1 5260 | befoul,-3 5261 | befriend,1 5262 | befuddle,-1 5263 | behead,-3 5264 | belabor,-1 5265 | belch,-1 5266 | beleaguer,-1 5267 | belie,-3 5268 | belittle,-3 5269 | bemoan,-2 5270 | besmirch,-2 5271 | bestow,2 5272 | betray,-4 5273 | beware,-2 5274 | bewilder,-3 5275 | bias,-2 5276 | bite,-2 5277 | blab,-1 5278 | blabber,-1 5279 | blacken,-1 5280 | blaspheme,-3 5281 | blast,-3 5282 | blather,-2 5283 | block,-2 5284 | bloom,1 5285 | blunder,-2 5286 | blur,-1 5287 | boast,2 5288 | bolster,2 5289 | bolt,-1 5290 | bombard,-3 5291 | boost,2 5292 | booze,-2 5293 | bore,-3 5294 | bother,-2 5295 | brag,-2 5296 | brainwash,-3 5297 | brandish,-1 5298 | breach,-1 5299 | bribe,-2 5300 | bristle,-2 5301 | browbeat,-3 5302 | bruise,-1 5303 | brutalize,-3 5304 | bug,-2 5305 | bungle,-2 5306 | butcher,-4 5307 | cancel,-1 5308 | cannibalize,-5 5309 | capitalize,1 5310 | capitivate,3 5311 | capsize,-3 5312 | capture,1 5313 | care,2 5314 | careen,-3 5315 | caress,2 5316 | carp,-1 5317 | celebrate,2 5318 | chafe,-2 5319 | challenge,-1 5320 | chastise,-1 5321 | cheapen,-2 5322 | cheat,-3 5323 | cherish,3 5324 | chide,-1 5325 | choke,-2 5326 | clash,-2 5327 | cleanse,1 5328 | clog,-1 5329 | coddle,-1 5330 | coerce,-2 5331 | collaborate,2 5332 | collapse,-2 5333 | collide,-1 5334 | collude,-2 5335 | combat,-1 5336 | comfort,1 5337 | commemorate,2 5338 | commend,3 5339 | commiserate,-2 5340 | commune,1 5341 | communicate,1 5342 | compel,-1 5343 | compensate,1 5344 | complain,-2 5345 | complement,1 5346 | complicate,-1 5347 | complicit,-2 5348 | compliment,2 5349 | compromise,1 5350 | conceal,-2 5351 | concoct,-1 5352 | condemn,-3 5353 | condone,1 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