├── .babelrc ├── .gitignore ├── LICENSE ├── NOTICE ├── README.md ├── build └── vaderSentiment.bundle.js ├── package-lock.json ├── package.json ├── src ├── index.js ├── vaderSentiment.js └── vader_lexicon.js ├── tests ├── SentiText_tests.js ├── SentimentIntensityAnalyzer_tests.js ├── allcap_differential_tests.js ├── is_upper_python_tests.js ├── negated_tests.js ├── normalize_tests.js └── scalar_inc_dec_tests.js ├── vader_lexicon.txt └── webpack.config.js /.babelrc: -------------------------------------------------------------------------------- 1 | { 2 | "presets": ["es2015"] 3 | } 4 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | .idea 2 | .DS_Store 3 | 4 | yarn.lock 5 | 6 | # Logs 7 | logs 8 | *.log 9 | npm-debug.log* 10 | yarn-debug.log* 11 | yarn-error.log* 12 | 13 | # Runtime data 14 | pids 15 | *.pid 16 | *.seed 17 | *.pid.lock 18 | 19 | # Directory for instrumented libs generated by jscoverage/JSCover 20 | lib-cov 21 | 22 | # Coverage directory used by tools like istanbul 23 | coverage 24 | 25 | # nyc test coverage 26 | .nyc_output 27 | 28 | # Grunt intermediate storage (http://gruntjs.com/creating-plugins#storing-task-files) 29 | .grunt 30 | 31 | # Bower dependency directory (https://bower.io/) 32 | bower_components 33 | 34 | # node-waf configuration 35 | .lock-wscript 36 | 37 | # Compiled binary addons (http://nodejs.org/api/addons.html) 38 | build/Release 39 | 40 | # Dependency directories 41 | node_modules/ 42 | jspm_packages/ 43 | 44 | # Typescript v1 declaration files 45 | typings/ 46 | 47 | # Optional npm cache directory 48 | .npm 49 | 50 | # Optional eslint cache 51 | .eslintcache 52 | 53 | # Optional REPL history 54 | .node_repl_history 55 | 56 | # Output of 'npm pack' 57 | *.tgz 58 | 59 | # Yarn Integrity file 60 | .yarn-integrity 61 | 62 | # dotenv environment variables file 63 | .env 64 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | Apache License 2 | Version 2.0, January 2004 3 | http://www.apache.org/licenses/ 4 | 5 | TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 6 | 7 | 1. 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(2014). VADER: A Parsimonious Rule-based Model for Sentiment Analysis of Social Media Text. Eighth International Conference on Weblogs and Social Media (ICWSM-14). Ann Arbor, MI, June 2014. 9 | 10 | 11 | ## License 12 | 13 | This JavaScript port of VADER is licensed under the terms of the [Apache-2.0 License](http://www.apache.org/licenses/LICENSE-2.0) 14 | 15 | ## Usage 16 | 17 | install via npm 18 | 19 | ``` 20 | npm install --save vader-sentiment 21 | ``` 22 | 23 | Example use: 24 | 25 | ``` 26 | const vader = require('vader-sentiment'); 27 | const input = 'VADER is very smart, handsome, and funny'; 28 | const intensity = vader.SentimentIntensityAnalyzer.polarity_scores(input); 29 | console.log(intensity); 30 | // {neg: 0.0, neu: 0.299, pos: 0.701, compound: 0.8545} 31 | ``` 32 | 33 | #### About the Scoring 34 | 35 | * The ``compound`` score is computed by summing the valence scores of each word in the lexicon, adjusted according to the rules, and then normalized to be between -1 (most extreme negative) and +1 (most extreme positive). This is the most useful metric if you want a single unidimensional measure of sentiment for a given sentence. Calling it a 'normalized, weighted composite score' is accurate. 36 | 37 | It is also useful for researchers who would like to set standardized thresholds for classifying sentences as either positive, neutral, or negative. 38 | Typical threshold values (used in the literature cited on this page) are: 39 | 40 | #. **positive sentiment**: ``compound`` score >= 0.05 41 | #. **neutral sentiment**: (``compound`` score > -0.05) and (``compound`` score < 0.05) 42 | #. **negative sentiment**: ``compound`` score <= -0.05 43 | 44 | * The ``pos``, ``neu``, and ``neg`` scores are ratios for proportions of text that fall in each category (so these should all add up to be 1... or close to it with float operation). These are the most useful metrics if you want multidimensional measures of sentiment for a given sentence. 45 | 46 | ## Development 47 | 48 | Install dependencies by running 49 | 50 | ``` 51 | npm install 52 | ``` 53 | 54 | To make code consistent 55 | 56 | ``` 57 | npm run prettier 58 | ``` 59 | 60 | For tests 61 | 62 | ``` 63 | npm run tests 64 | ``` 65 | -------------------------------------------------------------------------------- /build/vaderSentiment.bundle.js: -------------------------------------------------------------------------------- 1 | exports.SentimentIntensityAnalyzer=function(e){var s={};function i(r){if(s[r])return s[r].exports;var t=s[r]={i:r,l:!1,exports:{}};return e[r].call(t.exports,t,t.exports,i),t.l=!0,t.exports}return i.m=e,i.c=s,i.d=function(e,s,r){i.o(e,s)||Object.defineProperty(e,s,{configurable:!1,enumerable:!0,get:r})},i.r=function(e){Object.defineProperty(e,"__esModule",{value:!0})},i.n=function(e){var s=e&&e.__esModule?function(){return 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able:1.2,stabs:-1.9,stall:-.8,stalled:-.8,stalling:-.8,stamina:1.2,stammer:-.9,stammered:-.9,stammerer:-1.1,stammerers:-.8,stammering:-1,stammers:-.8,stampede:-1.8,stank:-1.9,startle:-1.3,startled:-.7,startlement:-.5,startlements:.2,startler:-.8,startlers:-.5,startles:-.5,startling:.3,startlingly:-.3,starve:-1.9,starved:-2.6,starves:-2.3,starving:-1.8,steadfast:1,steal:-2.2,stealable:-1.7,stealer:-1.7,stealers:-2.2,stealing:-2.7,stealings:-1.9,steals:-2.3,stealth:-.3,stealthier:-.3,stealthiest:.4,stealthily:.1,stealthiness:.2,stealths:-.3,stealthy:-.1,stench:-2.3,stenches:-1.5,stenchful:-2.4,stenchy:-2.3,stereotype:-1.3,stereotyped:-1.2,stifled:-1.4,stimulate:.9,stimulated:.9,stimulates:1,stimulating:1.9,stingy:-1.6,stink:-1.7,stinkard:-2.3,stinkards:-1,stinkbug:-.2,stinkbugs:-1,stinker:-1.5,stinkers:-1.2,stinkhorn:-.2,stinkhorns:-.8,stinkier:-1.5,stinkiest:-2.1,stinking:-2.4,stinkingly:-1.3,stinko:-1.5,stinkpot:-2.5,stinkpots:-.7,stinks:-1,stinkweed:-.4,stinkwood:-.1,stinky:-1.5,stolen:-2.2,stop:-1.2,stopped:-.9,stopping:-.6,stops:-.6,stout:.7,straight:.9,strain:-.2,strained:-1.7,strainer:-.8,strainers:-.3,straining:-1.3,strains:-1.2,strange:-.8,strangely:-1.2,strangled:-2.5,strength:2.2,strengthen:1.3,strengthened:1.8,strengthener:1.8,strengtheners:1.4,strengthening:2.2,strengthens:2,strengths:1.7,stress:-1.8,stressed:-1.4,stresses:-2,stressful:-2.3,stressfully:-2.6,stressing:-1.5,stressless:1.6,stresslessness:1.6,stressor:-1.8,stressors:-2.1,stricken:-2.3,strike:-.5,strikers:-.6,strikes:-1.5,strong:2.3,strongbox:.7,strongboxes:.3,stronger:1.6,strongest:1.9,stronghold:.5,strongholds:1,strongish:1.7,strongly:1.1,strongman:.7,strongmen:.5,strongyl:.6,strongyles:.2,strongyloidosis:-.8,strongyls:.1,struck:-1,struggle:-1.3,struggled:-1.4,struggler:-1.1,strugglers:-1.4,struggles:-1.5,struggling:-1.8,stubborn:-1.7,stubborner:-1.5,stubbornest:-.6,stubbornly:-1.4,stubbornness:-1.1,stubbornnesses:-1.5,stuck:-1,stunk:-1.6,stunned:-.4,stunning:1.6,stuns:.1,stupid:-2.4,stupider:-2.5,stupidest:-2.4,stupidities:-2,stupidity:-1.9,stupidly:-2,stupidness:-1.7,stupidnesses:-2.6,stupids:-2.3,stutter:-1,stuttered:-.9,stutterer:-1,stutterers:-1.1,stuttering:-1.3,stutters:-1,suave:2,submissive:-1.3,submissively:-1,submissiveness:-.7,substantial:.8,subversive:-.9,succeed:2.2,succeeded:1.8,succeeder:1.2,succeeders:1.3,succeeding:2.2,succeeds:2.2,success:2.7,successes:2.6,successful:2.8,successfully:2.2,successfulness:2.7,succession:.8,successional:.9,successionally:1.1,successions:.1,successive:1.1,successively:.9,successiveness:1,successor:.9,successors:1.1,suck:-1.9,sucked:-2,sucker:-2.4,suckered:-2,suckering:-2.1,suckers:-2.3,sucks:-1.5,sucky:-1.9,suffer:-2.5,suffered:-2.2,sufferer:-2,sufferers:-2.4,suffering:-2.1,suffers:-2.1,suicidal:-3.5,suicide:-3.5,suing:-1.1,sulking:-1.5,sulky:-.8,sullen:-1.7,sunnier:2.3,sunniest:2.4,sunny:1.8,sunshine:2.2,sunshiny:1.9,super:2.9,superb:3.1,superior:2.5,superiorities:.8,superiority:1.4,superiorly:2.2,superiors:1,support:1.7,supported:1.3,supporter:1.1,supporters:1.9,supporting:1.9,supportive:1.2,supportiveness:1.5,supports:1.5,supremacies:.8,supremacist:.5,supremacists:-1,supremacy:.2,suprematists:.4,supreme:2.6,supremely:2.7,supremeness:2.3,supremer:2.3,supremest:2.2,supremo:1.9,supremos:1.3,sure:1.3,surefire:1,surefooted:1.9,surefootedly:1.6,surefootedness:1.5,surely:1.9,sureness:2,surer:1.2,surest:1.3,sureties:1.3,surety:1,suretyship:-.1,suretyships:.4,surprisal:1.5,surprisals:.7,surprise:1.1,surprised:.9,surpriser:.6,surprisers:.3,surprises:.9,surprising:1.1,surprisingly:1.2,survived:2.3,surviving:1.2,survivor:1.5,suspect:-1.2,suspected:-.9,suspecting:-.7,suspects:-1.4,suspend:-1.3,suspended:-2.1,suspicion:-1.6,suspicions:-1.5,suspicious:-1.5,suspiciously:-1.7,suspiciousness:-1.2,sux:-1.5,swear:-.2,swearing:-1,swears:.2,sweet:2,"sweet<3":3,sweetheart:3.3,sweethearts:2.8,sweetie:2.2,sweeties:2.1,sweetly:2.1,sweetness:2.2,sweets:2.2,swift:.8,swiftly:1.2,swindle:-2.4,swindles:-1.5,swindling:-2,sympathetic:2.3,sympathy:1.5,talent:1.8,talented:2.3,talentless:-1.6,talents:2,tantrum:-1.8,tantrums:-1.5,tard:-2.5,tears:-.9,teas:.3,tease:-1.3,teased:-1.2,teasel:-.1,teaseled:-.8,teaseler:-.8,teaselers:-1.2,teaseling:-.4,teaselled:-.4,teaselling:-.2,teasels:-.1,teaser:-1,teasers:-.7,teases:-1.2,teashops:.2,teasing:-.3,teasingly:-.4,teaspoon:.2,teaspoonful:.2,teaspoonfuls:.4,teaspoons:.5,teaspoonsful:.3,temper:-1.8,tempers:-1.3,tendered:.5,tenderer:.6,tenderers:1.2,tenderest:1.4,tenderfeet:-.4,tenderfoot:-.1,tenderfoots:-.5,tenderhearted:1.5,tenderheartedly:2.7,tenderheartedness:.7,tenderheartednesses:2.8,tendering:.6,tenderization:.2,tenderize:.1,tenderized:.1,tenderizer:.4,tenderizes:.3,tenderizing:.3,tenderloin:-.2,tenderloins:.4,tenderly:1.8,tenderness:1.8,tendernesses:.9,tenderometer:.2,tenderometers:.2,tenders:.6,tense:-1.4,tensed:-1,tensely:-1.2,tenseness:-1.5,tenser:-1.5,tenses:-.9,tensest:-1.2,tensing:-1,tension:-1.3,tensional:-.8,tensioned:-.4,tensioner:-1.6,tensioners:-.9,tensioning:-1.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r=0;ri&&(s.splice(t,1),s.splice(t,0,1.5*n))}return s}},{key:"idioms_check",value:function(e,s,i){for(var r=s[i-1]+" "+s[i],t=s[i-2]+" "+s[i-1]+" "+s[i],n=s[i-2]+" "+s[i-1],a=s[i-3]+" "+s[i-2]+" "+s[i-1],o=s[i-3]+" "+s[i-2],d=[r,t,n,a,o],u=0;ui){var c=s[i]+" "+s[i+1];p.hasOwnProperty(c)&&(e=p[c])}if(s.length-1>i+1){var g=s[i]+" "+s[i+1]+" "+s[i+2];p.hasOwnProperty(g)&&(e=p[g])}return(m.hasOwnProperty(o)||m.hasOwnProperty(n))&&(e+=l),e}},{key:"never_check",value:function(e,s,i,r){return 0===i&&h([s[r-1]])&&(e*=d),1===i&&("never"!==s[r-2]||"so"!==s[r-1]&&"this"!==s[r-1]?h([s[r-(i+1)]])&&(e*=d):e*=1.5),2===i&&("never"===s[r-3]&&("so"===s[r-2]||"this"===s[r-2])||"so"===s[r-1]||"this"===s[r-1]?e*=1.25:h([s[r-(i+1)]])&&(e*=d)),e}},{key:"punctuation_emphasis",value:function(s,i){return e.amplify_ep(i)+e.amplify_qm(i)}},{key:"amplify_ep",value:function(e){var s=e.replace(/[^!]/g,"").length;return s>4&&(s=4),.292*s}},{key:"amplify_qm",value:function(e){var s=e.replace(/[^?]/g,"").length,i=0;return s>1&&(i=s<=3?.18*s:.96),i}},{key:"sift_sentiment_scores",value:function(e){for(var s=0,i=0,r=0,t=0;t0?s+=n+1:n<0?i+=n-1:r+=1}return[s,i,r]}},{key:"score_valence",value:function(s,i){if(s&&s.length>0){for(var r=0,t=0;t0?r+=n:r<0&&(r-=n);var a=f(r),l=e.sift_sentiment_scores(s),o=l[0],d=l[1],u=l[2];o>Math.abs(d)?o+=n:o" 23 | ], 24 | "license": "Apache-2.0", 25 | "bugs": { 26 | "url": "https://github.com/vaderSentiment/vaderSentiment-js/issues" 27 | }, 28 | "dependencies": {}, 29 | "devDependencies": { 30 | "babel-cli": "^6.26.0", 31 | "babel-core": "^6.26.0", 32 | "babel-loader": "^7.1.4", 33 | "babel-preset-es2015": "^6.24.1", 34 | "babel-tape-runner": "^2.0.1", 35 | "faucet": "^0.0.1", 36 | "prettier": "^1.9.2", 37 | "tape": "^4.8.0", 38 | "webpack": "^4.5.0", 39 | "webpack-cli": "^2.0.14" 40 | } 41 | } 42 | -------------------------------------------------------------------------------- /src/index.js: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright 2018 Comcast Cable Communications Management, LLC 3 | * Licensed under the Apache License, Version 2.0 (the "License"); 4 | * you may not use this file except in compliance with the License. 5 | * You may obtain a copy of the License at 6 | * http://www.apache.org/licenses/LICENSE-2.0 7 | * Unless required by applicable law or agreed to in writing, software 8 | * distributed under the License is distributed on an "AS IS" BASIS, 9 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 10 | * See the License for the specific language governing permissions and 11 | * limitations under the License. 12 | */ 13 | 14 | /** 15 | Javascript port of vader sentiment analysis tool, source: 16 | Hutto, C.J. & Gilbert, E.E. (2014). VADER: A Parsimonious Rule-based Model for 17 | Sentiment Analysis of Social Media Text. Eighth International Conference on 18 | Weblogs and Social Media (ICWSM-14). Ann Arbor, MI, June 2014. 19 | */ 20 | 21 | import {SentimentIntensityAnalyzer} from './vaderSentiment.js'; 22 | export default SentimentIntensityAnalyzer; 23 | -------------------------------------------------------------------------------- /src/vaderSentiment.js: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright 2018 Comcast Cable Communications Management, LLC 3 | * Licensed under the Apache License, Version 2.0 (the "License"); 4 | * you may not use this file except in compliance with the License. 5 | * You may obtain a copy of the License at 6 | * http://www.apache.org/licenses/LICENSE-2.0 7 | * Unless required by applicable law or agreed to in writing, software 8 | * distributed under the License is distributed on an "AS IS" BASIS, 9 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 10 | * See the License for the specific language governing permissions and 11 | * limitations under the License. 12 | */ 13 | 14 | /** 15 | Javascript port of vader sentiment analysis tool, source: 16 | Hutto, C.J. & Gilbert, E.E. (2014). VADER: A Parsimonious Rule-based Model for 17 | Sentiment Analysis of Social Media Text. Eighth International Conference on 18 | Weblogs and Social Media (ICWSM-14). Ann Arbor, MI, June 2014. 19 | */ 20 | 21 | // Constants 22 | 23 | const LEXICON = require('./vader_lexicon.js').lexicon; 24 | 25 | // (empirically derived mean sentiment intensity rating increase for booster words) 26 | export const B_INCR = 0.293; 27 | 28 | export const B_DECR = -0.293; 29 | 30 | // (empirically derived mean sentiment intensity rating increase for using 31 | // ALLCAPs to emphasize a word) 32 | export const C_INCR = 0.733; 33 | 34 | export const N_SCALAR = -0.74; 35 | 36 | export const REGEX_REMOVE_PUNCTUATION = new RegExp(/[!"#$%&'()*+,-./:;<=>?@[\\\]^_`{|}~]/g); 37 | // ` // <- to fix ide thinking grave accent in regex is starting a template quote 38 | 39 | export const PUNC_LIST = [ 40 | '.', 41 | '!', 42 | '?', 43 | ',', 44 | ';', 45 | ':', 46 | '-', 47 | "'", 48 | '"', 49 | '!!', 50 | '!!!', 51 | '??', 52 | '???', 53 | '?!?', 54 | '!?!', 55 | '?!?!', 56 | '!?!?' 57 | ]; 58 | 59 | export const NEGATE = [ 60 | 'aint', 61 | 'arent', 62 | 'cannot', 63 | 'cant', 64 | 'couldnt', 65 | 'darent', 66 | 'didnt', 67 | 'doesnt', 68 | "ain't", 69 | "aren't", 70 | "can't", 71 | "couldn't", 72 | "daren't", 73 | "didn't", 74 | "doesn't", 75 | 'dont', 76 | 'hadnt', 77 | 'hasnt', 78 | 'havent', 79 | 'isnt', 80 | 'mightnt', 81 | 'mustnt', 82 | 'neither', 83 | "don't", 84 | "hadn't", 85 | "hasn't", 86 | "haven't", 87 | "isn't", 88 | "mightn't", 89 | "mustn't", 90 | 'neednt', 91 | "needn't", 92 | 'never', 93 | 'none', 94 | 'nope', 95 | 'nor', 96 | 'not', 97 | 'nothing', 98 | 'nowhere', 99 | 'oughtnt', 100 | 'shant', 101 | 'shouldnt', 102 | 'uhuh', 103 | 'wasnt', 104 | 'werent', 105 | "oughtn't", 106 | "shan't", 107 | "shouldn't", 108 | 'uh-uh', 109 | "wasn't", 110 | "weren't", 111 | 'without', 112 | 'wont', 113 | 'wouldnt', 114 | "won't", 115 | "wouldn't", 116 | 'rarely', 117 | 'seldom', 118 | 'despite' 119 | ]; 120 | 121 | // booster/dampener 'intensifiers' or 'degree adverbs' 122 | // http://en.wiktionary.org/wiki/Category:English_degree_adverbs 123 | 124 | export const BOOSTER_DICT = { 125 | absolutely: B_INCR, 126 | amazingly: B_INCR, 127 | awfully: B_INCR, 128 | completely: B_INCR, 129 | considerably: B_INCR, 130 | decidedly: B_INCR, 131 | deeply: B_INCR, 132 | effing: B_INCR, 133 | enormously: B_INCR, 134 | entirely: B_INCR, 135 | especially: B_INCR, 136 | exceptionally: B_INCR, 137 | extremely: B_INCR, 138 | fabulously: B_INCR, 139 | flipping: B_INCR, 140 | flippin: B_INCR, 141 | fricking: B_INCR, 142 | frickin: B_INCR, 143 | frigging: B_INCR, 144 | friggin: B_INCR, 145 | fully: B_INCR, 146 | fucking: B_INCR, 147 | greatly: B_INCR, 148 | hella: B_INCR, 149 | highly: B_INCR, 150 | hugely: B_INCR, 151 | incredibly: B_INCR, 152 | intensely: B_INCR, 153 | majorly: B_INCR, 154 | more: B_INCR, 155 | most: B_INCR, 156 | particularly: B_INCR, 157 | purely: B_INCR, 158 | quite: B_INCR, 159 | really: B_INCR, 160 | remarkably: B_INCR, 161 | so: B_INCR, 162 | substantially: B_INCR, 163 | thoroughly: B_INCR, 164 | totally: B_INCR, 165 | tremendously: B_INCR, 166 | uber: B_INCR, 167 | unbelievably: B_INCR, 168 | unusually: B_INCR, 169 | utterly: B_INCR, 170 | very: B_INCR, 171 | almost: B_DECR, 172 | barely: B_DECR, 173 | hardly: B_DECR, 174 | 'just enough': B_DECR, 175 | 'kind of': B_DECR, 176 | kinda: B_DECR, 177 | kindof: B_DECR, 178 | 'kind-of': B_DECR, 179 | less: B_DECR, 180 | little: B_DECR, 181 | marginally: B_DECR, 182 | occasionally: B_DECR, 183 | partly: B_DECR, 184 | scarcely: B_DECR, 185 | slightly: B_DECR, 186 | somewhat: B_DECR, 187 | 'sort of': B_DECR, 188 | sorta: B_DECR, 189 | sortof: B_DECR, 190 | 'sort-of': B_DECR 191 | }; 192 | 193 | // check for special case idioms using a sentiment-laden keyword known to VADER 194 | export const SPECIAL_CASE_IDIOMS = { 195 | 'the shit': 3, 196 | 'the bomb': 3, 197 | 'bad ass': 1.5, 198 | 'yeah right': -2, 199 | 'cut the mustard': 2, 200 | 'kiss of death': -1.5, 201 | 'hand to mouth': -2 202 | }; 203 | 204 | // static methods 205 | 206 | export const negated = (input_words, include_nt = true) => { 207 | /** 208 | Determine if input contains negation words 209 | */ 210 | 211 | let neg_words = []; 212 | neg_words.push.apply(neg_words, NEGATE); 213 | for (let i = 0; i < neg_words.length; i++) { 214 | if (input_words.indexOf(neg_words[i]) >= 0) { 215 | return true; 216 | } 217 | } 218 | if (include_nt === true) { 219 | for (let i = 0; i < input_words.length; i++) { 220 | if (input_words[i].indexOf("n't") >= 0) { 221 | return true; 222 | } 223 | } 224 | } 225 | const i = input_words.findIndex(element => { 226 | return element === 'least'; 227 | }); 228 | return i !== -1 && i > 0 && input_words[i - 1] !== 'at'; 229 | }; 230 | 231 | export const normalize = (score, alpha = 15) => { 232 | /** 233 | Normalize the score to be between -1 and 1 using an alpha that 234 | approximates the max expected value 235 | */ 236 | 237 | const norm_score = score / Math.sqrt(score * score + alpha); 238 | if (norm_score < -1.0) { 239 | return -1.0; 240 | } else if (norm_score > 1.0) { 241 | return 1.0; 242 | } else { 243 | return norm_score; 244 | } 245 | }; 246 | 247 | export const allcap_differential = words => { 248 | /** 249 | Check whether just some words in the input are ALL CAPS 250 | */ 251 | 252 | let allcap_words = 0; 253 | for (let i = 0; i < words.length; i++) { 254 | if (is_upper_python(words[i])) { 255 | allcap_words += 1; 256 | } 257 | } 258 | const cap_differential = words.length - allcap_words; 259 | return cap_differential > 0 && cap_differential < words.length; 260 | }; 261 | 262 | export const scalar_inc_dec = (word, valence, is_cap_diff) => { 263 | /** 264 | Check if the preceding words increase, decrease, or negate/nullify the 265 | valence 266 | */ 267 | 268 | let scalar = 0.0; 269 | const word_lower = word.toLowerCase(); 270 | if (BOOSTER_DICT.hasOwnProperty(word_lower)) { 271 | scalar = BOOSTER_DICT[word_lower]; 272 | if (valence < 0) { 273 | scalar *= -1; 274 | } 275 | // check if booster/dampener word is in ALLCAPS (while others aren't) 276 | if (is_cap_diff && is_upper_python(word)) { 277 | if (valence > 0) { 278 | scalar += C_INCR; 279 | } else { 280 | scalar -= C_INCR; 281 | } 282 | } 283 | } 284 | return scalar; 285 | }; 286 | 287 | export const is_upper_python = word => { 288 | /** 289 | Python style "isupper" function. Requirements are that the string is at least one character in length, 290 | and does not consider an emoticon, e.g. :), as an uppercase word, but a string with special characters and only 291 | all caps characters is an uppercase word, e.g. ':)WORD' is true 292 | */ 293 | if (typeof word === 'string' || word instanceof String) { 294 | if (word.length > 0) { 295 | return /^[^a-z]*[A-Z]+[^a-z]*$/g.test(word); 296 | } 297 | } 298 | return false; 299 | }; 300 | 301 | export class SentiText { 302 | /** 303 | Identify sentiment-relevant string-level properties of input text 304 | */ 305 | constructor(text) { 306 | this.text = text; 307 | this.words_and_emoticons = this.get_words_and_emoticons(); 308 | // doesn't separate words from adjacent punctuation (keeps emoticons & contractions) 309 | this.is_cap_diff = allcap_differential(this.words_and_emoticons); 310 | } 311 | 312 | get_words_plus_punc() { 313 | /** 314 | Returns mapping of form: 315 | { 316 | 'cat,': 'cat', 317 | ',cat': 'cat' 318 | } 319 | */ 320 | 321 | // removes punctuation (but loses emoticons & contractions) 322 | const no_punc_text = this.text.slice(0).replace(REGEX_REMOVE_PUNCTUATION, ''); 323 | const words = no_punc_text.split(/\s/); 324 | // removes singletons 325 | const words_only = words.filter(word => { 326 | return word.length > 1; 327 | }); 328 | let words_punc_dict = {}; 329 | for (let j = 0; j < PUNC_LIST.length; j++) { 330 | for (let k = 0; k < words_only.length; k++) { 331 | let pb = `${PUNC_LIST[j]}${words_only[k]}`; 332 | let pa = `${words_only[k]}${PUNC_LIST[j]}`; 333 | words_punc_dict[pb] = words_only[k]; 334 | words_punc_dict[pa] = words_only[k]; 335 | } 336 | } 337 | return words_punc_dict; 338 | } 339 | 340 | get_words_and_emoticons() { 341 | /** 342 | Removes leading and trailing puncutation 343 | Leaves contractions and most emoticons 344 | Does not preserve punc-plus-letter emoticons (e.g. :D) 345 | */ 346 | 347 | const tokens = this.text.split(/\s/); 348 | const words_punc_dict = this.get_words_plus_punc(); 349 | let words_only = tokens.filter(token => { 350 | return token.length > 1; 351 | }); 352 | for (let i = 0; i < words_only.length; i++) { 353 | if (words_punc_dict.hasOwnProperty(words_only[i])) { 354 | words_only[i] = words_punc_dict[words_only[i]]; 355 | } 356 | } 357 | return words_only; 358 | } 359 | } 360 | 361 | export class SentimentIntensityAnalyzer { 362 | /** 363 | Give a sentiment intensity score to sentences 364 | */ 365 | 366 | static polarity_scores(text) { 367 | /** 368 | Return a float for sentiment strength based on the input text. 369 | Positive values are positive valence, negative value are negative 370 | valence 371 | */ 372 | 373 | const sentiText = new SentiText(text); 374 | let sentiments = []; 375 | const words_and_emoticons = sentiText.words_and_emoticons; 376 | for (let i = 0; i < words_and_emoticons.length; i++) { 377 | let valence = 0; 378 | const item = words_and_emoticons[i]; 379 | if ( 380 | (i < words_and_emoticons.length - 1 && 381 | item.toLowerCase() === 'kind' && 382 | words_and_emoticons[i + 1].toLowerCase() === 'of') || 383 | BOOSTER_DICT.hasOwnProperty(item.toLowerCase()) 384 | ) { 385 | sentiments.push(valence); 386 | continue; 387 | } 388 | 389 | sentiments = SentimentIntensityAnalyzer.sentiment_valence( 390 | valence, 391 | sentiText, 392 | item, 393 | i, 394 | sentiments 395 | ); 396 | } 397 | 398 | sentiments = SentimentIntensityAnalyzer.but_check(words_and_emoticons, sentiments); 399 | const valence_dict = SentimentIntensityAnalyzer.score_valence(sentiments, text); 400 | return valence_dict; 401 | } 402 | 403 | static sentiment_valence(valence, sentiText, item, index, sentiments) { 404 | const is_cap_diff = sentiText.is_cap_diff; 405 | const words_and_emoticons = sentiText.words_and_emoticons; 406 | const item_lowercase = item.toLowerCase(); 407 | if (LEXICON.hasOwnProperty(item_lowercase)) { 408 | // get the sentiment valence 409 | valence = LEXICON[item_lowercase]; 410 | // check if sentiment laden word is in ALL CAPS (while others aren't) 411 | if (is_upper_python(item) && is_cap_diff) { 412 | if (valence > 0) { 413 | valence += C_INCR; 414 | } else { 415 | valence -= C_INCR; 416 | } 417 | } 418 | 419 | for (let start_i = 0; start_i < 3; start_i++) { 420 | if ( 421 | index > start_i && 422 | LEXICON.hasOwnProperty(words_and_emoticons[index - (start_i + 1)].toLowerCase()) === false 423 | ) { 424 | // dampen the scalar modifier of preceding words and emoticons 425 | // (excluding the ones that immediately preceed the item) based 426 | // on their distance from the current item. 427 | let s = scalar_inc_dec(words_and_emoticons[index - (start_i + 1)], valence, is_cap_diff); 428 | if (start_i === 1 && s !== 0) { 429 | s = s * 0.95; 430 | } else if (start_i === 2 && s !== 0) { 431 | s = s * 0.9; 432 | } 433 | valence = valence + s; 434 | valence = this.never_check(valence, words_and_emoticons, start_i, index); 435 | if (start_i === 2) { 436 | valence = this.idioms_check(valence, words_and_emoticons, index); 437 | } 438 | } 439 | } 440 | 441 | valence = this.least_check(valence, words_and_emoticons, index); 442 | } 443 | 444 | sentiments.push(valence); 445 | return sentiments; 446 | } 447 | 448 | static least_check(valence, words_and_emoticons, index) { 449 | /** 450 | Check for negaion case using "least" 451 | */ 452 | 453 | if ( 454 | index > 1 && 455 | words_and_emoticons[index - 1].toLowerCase() === 'least' && 456 | LEXICON.hasOwnProperty(words_and_emoticons[index - 1].toLowerCase()) === false 457 | ) { 458 | if ( 459 | words_and_emoticons[index - 2].toLowerCase() !== 'at' && 460 | words_and_emoticons[index - 2].toLowerCase() !== 'very' 461 | ) { 462 | valence = valence * N_SCALAR; 463 | } 464 | } else if ( 465 | index > 0 && 466 | words_and_emoticons[index - 1].toLowerCase() === 'least' && 467 | LEXICON.hasOwnProperty(words_and_emoticons[index - 1].toLowerCase()) === false 468 | ) { 469 | valence = valence * N_SCALAR; 470 | } 471 | 472 | return valence; 473 | } 474 | 475 | static but_check(words_and_emoticons, sentiments) { 476 | /** 477 | Check for modification in sentiment due to contrastive conjunction 'but' 478 | */ 479 | let but_index = words_and_emoticons.indexOf('but'); 480 | if (but_index === -1) { 481 | but_index = words_and_emoticons.indexOf('BUT'); 482 | } 483 | if (but_index !== -1) { 484 | for (let i = 0; i < sentiments.length; i++) { 485 | const sentiment_index = i; 486 | const sentiment = sentiments[sentiment_index]; 487 | if (sentiment_index < but_index) { 488 | sentiments.splice(sentiment_index, 1); 489 | sentiments.splice(sentiment_index, 0, sentiment * 0.5); 490 | } else if (sentiment_index > but_index) { 491 | sentiments.splice(sentiment_index, 1); 492 | sentiments.splice(sentiment_index, 0, sentiment * 1.5); 493 | } 494 | } 495 | } 496 | return sentiments; 497 | } 498 | 499 | static idioms_check(valence, words_and_emoticons, index) { 500 | const onezero = `${words_and_emoticons[index - 1]} ${words_and_emoticons[index]}`; 501 | const twoonezero = `${words_and_emoticons[index - 2]} ${words_and_emoticons[index - 1]} ${ 502 | words_and_emoticons[index] 503 | }`; 504 | const twoone = `${words_and_emoticons[index - 2]} ${words_and_emoticons[index - 1]}`; 505 | const threetwoone = `${words_and_emoticons[index - 3]} ${words_and_emoticons[index - 2]} ${ 506 | words_and_emoticons[index - 1] 507 | }`; 508 | const threetwo = `${words_and_emoticons[index - 3]} ${words_and_emoticons[index - 2]}`; 509 | 510 | const sequences = [onezero, twoonezero, twoone, threetwoone, threetwo]; 511 | 512 | for (let i = 0; i < sequences.length; i++) { 513 | if (SPECIAL_CASE_IDIOMS.hasOwnProperty(sequences[i])) { 514 | valence = SPECIAL_CASE_IDIOMS[sequences[i]]; 515 | break; 516 | } 517 | } 518 | 519 | if (words_and_emoticons.length - 1 > index) { 520 | const zeroone = `${words_and_emoticons[index]} ${words_and_emoticons[index + 1]}`; 521 | if (SPECIAL_CASE_IDIOMS.hasOwnProperty(zeroone)) { 522 | valence = SPECIAL_CASE_IDIOMS[zeroone]; 523 | } 524 | } 525 | 526 | if (words_and_emoticons.length - 1 > index + 1) { 527 | const zeroonetwo = `${words_and_emoticons[index]} ${words_and_emoticons[index + 1]} ${ 528 | words_and_emoticons[index + 2] 529 | }`; 530 | if (SPECIAL_CASE_IDIOMS.hasOwnProperty(zeroonetwo)) { 531 | valence = SPECIAL_CASE_IDIOMS[zeroonetwo]; 532 | } 533 | } 534 | 535 | // check for booster/dampener bi-grams such as 'sort of' or 'kind of' 536 | if (BOOSTER_DICT.hasOwnProperty(threetwo) || BOOSTER_DICT.hasOwnProperty(twoone)) { 537 | valence = valence + B_DECR; 538 | } 539 | 540 | return valence; 541 | } 542 | 543 | static never_check(valence, words_and_emoticons, start_i, index) { 544 | if (start_i === 0) { 545 | if (negated([words_and_emoticons[index - 1]])) { 546 | valence = valence * N_SCALAR; 547 | } 548 | } 549 | 550 | if (start_i === 1) { 551 | if ( 552 | words_and_emoticons[index - 2] === 'never' && 553 | (words_and_emoticons[index - 1] === 'so' || words_and_emoticons[index - 1] === 'this') 554 | ) { 555 | valence = valence * 1.5; 556 | } else if (negated([words_and_emoticons[index - (start_i + 1)]])) { 557 | valence = valence * N_SCALAR; 558 | } 559 | } 560 | 561 | if (start_i === 2) { 562 | if ( 563 | (words_and_emoticons[index - 3] === 'never' && 564 | (words_and_emoticons[index - 2] === 'so' || words_and_emoticons[index - 2] === 'this')) || 565 | (words_and_emoticons[index - 1] === 'so' || words_and_emoticons[index - 1] === 'this') 566 | ) { 567 | valence = valence * 1.25; 568 | } else if (negated([words_and_emoticons[index - (start_i + 1)]])) { 569 | valence = valence * N_SCALAR; 570 | } 571 | } 572 | 573 | return valence; 574 | } 575 | 576 | static punctuation_emphasis(sum_s, text) { 577 | /** 578 | Add emphasis from exclamation points and question marks 579 | */ 580 | 581 | const ep_amplifier = SentimentIntensityAnalyzer.amplify_ep(text); 582 | const qm_amplifier = SentimentIntensityAnalyzer.amplify_qm(text); 583 | const punct_emph_amplifier = ep_amplifier + qm_amplifier; 584 | return punct_emph_amplifier; 585 | } 586 | 587 | static amplify_ep(text) { 588 | /** 589 | Check for added emphasis resulting from exclamation points (up to 4 of them) 590 | */ 591 | 592 | let ep_count = text.replace(/[^!]/g, '').length; 593 | if (ep_count > 4) { 594 | ep_count = 4; 595 | } 596 | // empirically derived mean sentiment intensity rating increase for exclamation points 597 | const ep_amplifier = ep_count * 0.292; 598 | return ep_amplifier; 599 | } 600 | 601 | static amplify_qm(text) { 602 | /** 603 | Check for added emphasis resulting from question marks (2 or 3+) 604 | */ 605 | 606 | let qm_count = text.replace(/[^?]/g, '').length; 607 | let qm_amplifier = 0; 608 | if (qm_count > 1) { 609 | if (qm_count <= 3) { 610 | // empirically derived mean sentiment intensity rating increase for question marks 611 | qm_amplifier = qm_count * 0.18; 612 | } else { 613 | qm_amplifier = 0.96; 614 | } 615 | } 616 | 617 | return qm_amplifier; 618 | } 619 | 620 | static sift_sentiment_scores(sentiments) { 621 | /** 622 | Want separate positive versus negative sentiment scores 623 | */ 624 | 625 | let pos_sum = 0.0; 626 | let neg_sum = 0.0; 627 | let neu_count = 0; 628 | 629 | for (let i = 0; i < sentiments.length; i++) { 630 | const sentiment_score = sentiments[i]; 631 | if (sentiment_score > 0) { 632 | pos_sum += sentiment_score + 1; // compensates for neutral words that are counted as 1 633 | } else if (sentiment_score < 0) { 634 | neg_sum += sentiment_score - 1; // when used with math.fabs(), compensates for neutrals 635 | } else { 636 | neu_count += 1; 637 | } 638 | } 639 | const results = [pos_sum, neg_sum, neu_count]; 640 | return results; 641 | } 642 | 643 | static score_valence(sentiments, text) { 644 | if (sentiments && sentiments.length > 0) { 645 | let sum_s = 0; 646 | for (let i = 0; i < sentiments.length; i++) { 647 | sum_s += sentiments[i]; 648 | } 649 | // compute and add emphasis from punctuation in text 650 | const punct_emph_amplifier = SentimentIntensityAnalyzer.punctuation_emphasis(sum_s, text); 651 | if (sum_s > 0) { 652 | sum_s += punct_emph_amplifier; 653 | } else if (sum_s < 0) { 654 | sum_s -= punct_emph_amplifier; 655 | } 656 | 657 | let compound = normalize(sum_s); 658 | // discriminate between positive, negative and neutral sentiment scores 659 | let scores = SentimentIntensityAnalyzer.sift_sentiment_scores(sentiments); 660 | let pos_sum = scores[0]; 661 | let neg_sum = scores[1]; 662 | let neu_count = scores[2]; 663 | 664 | if (pos_sum > Math.abs(neg_sum)) { 665 | pos_sum += punct_emph_amplifier; 666 | } else if (pos_sum < Math.abs(neg_sum)) { 667 | neg_sum -= punct_emph_amplifier; 668 | } 669 | 670 | const total = pos_sum + Math.abs(neg_sum) + neu_count; 671 | const pos = Math.abs(pos_sum / total); 672 | const neg = Math.abs(neg_sum / total); 673 | const neu = Math.abs(neu_count / total); 674 | const sentiment_dict = { 675 | neg: parseFloat(neg.toFixed(3)), 676 | neu: parseFloat(neu.toFixed(3)), 677 | pos: parseFloat(pos.toFixed(3)), 678 | compound: parseFloat(compound.toFixed(4)) 679 | }; 680 | 681 | return sentiment_dict; 682 | } else { 683 | const sentiment_dict = { 684 | neg: 0.0, 685 | neu: 0.0, 686 | pos: 0.0, 687 | compound: 0.0 688 | }; 689 | 690 | return sentiment_dict; 691 | } 692 | } 693 | } 694 | -------------------------------------------------------------------------------- /tests/SentiText_tests.js: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright 2018 Comcast Cable Communications Management, LLC 3 | * Licensed under the Apache License, Version 2.0 (the "License"); 4 | * you may not use this file except in compliance with the License. 5 | * You may obtain a copy of the License at 6 | * http://www.apache.org/licenses/LICENSE-2.0 7 | * Unless required by applicable law or agreed to in writing, software 8 | * distributed under the License is distributed on an "AS IS" BASIS, 9 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 10 | * See the License for the specific language governing permissions and 11 | * limitations under the License. 12 | */ 13 | 14 | import {scalar_inc_dec, SentiText, PUNC_LIST} from '../src/vaderSentiment'; 15 | let test = require('tape'); 16 | 17 | test('SentiText.get_words_plus_punc returns empty dict if given no words', t => { 18 | const input = ''; 19 | const sentiText = new SentiText(input); 20 | const output = sentiText.get_words_plus_punc(); 21 | const expected = {}; 22 | 23 | t.deepEquals(output, expected); 24 | t.end(); 25 | }); 26 | 27 | test('SentiText.get_words_plus_punc creates punct dict for word', t => { 28 | const input = 'word'; 29 | const sentiText = new SentiText(input); 30 | const output = sentiText.get_words_plus_punc(); 31 | const expected = { 32 | '.word': 'word', 33 | 'word.': 'word', 34 | '!word': 'word', 35 | 'word!': 'word', 36 | '?word': 'word', 37 | 'word?': 'word', 38 | ',word': 'word', 39 | 'word,': 'word', 40 | ';word': 'word', 41 | 'word;': 'word', 42 | ':word': 'word', 43 | 'word:': 'word', 44 | '-word': 'word', 45 | 'word-': 'word', 46 | "'word": 'word', 47 | "word'": 'word', 48 | '"word': 'word', 49 | 'word"': 'word', 50 | '!!word': 'word', 51 | 'word!!': 'word', 52 | '!!!word': 'word', 53 | 'word!!!': 'word', 54 | '??word': 'word', 55 | 'word??': 'word', 56 | '???word': 'word', 57 | 'word???': 'word', 58 | '?!?word': 'word', 59 | 'word?!?': 'word', 60 | '!?!word': 'word', 61 | 'word!?!': 'word', 62 | '?!?!word': 'word', 63 | 'word?!?!': 'word', 64 | '!?!?word': 'word', 65 | 'word!?!?': 'word' 66 | }; 67 | const expected_num_elements = PUNC_LIST.length * input.split(/\s/).length * 2; 68 | 69 | t.equals(Object.keys(expected).length, expected_num_elements); 70 | t.equals(Object.keys(output).length, expected_num_elements); 71 | 72 | t.deepEquals(output, expected); 73 | t.end(); 74 | }); 75 | 76 | test('SentiText.get_words_plus_punc creates right size punct dict for multiple words', t => { 77 | const input = 'multiple words test'; 78 | const sentiText = new SentiText(input); 79 | const output = sentiText.get_words_plus_punc(); 80 | const expected_num_elements = PUNC_LIST.length * input.split(/\s/).length * 2; 81 | 82 | t.equals(Object.keys(output).length, expected_num_elements); 83 | t.end(); 84 | }); 85 | 86 | test('SentiText.get_words_plus_punc removes singletons', t => { 87 | const input = 'a b c'; 88 | const sentiText = new SentiText(input); 89 | const output = sentiText.get_words_plus_punc(); 90 | const expected_num_elements = 0; 91 | 92 | t.equals(Object.keys(output).length, expected_num_elements); 93 | t.end(); 94 | }); 95 | 96 | test('SentiText.get_words_and_emoticons preserves non punctuation emoticons', t => { 97 | const input = 'an emoticon 8D'; 98 | const sentiText = new SentiText(input); 99 | const output = sentiText.get_words_and_emoticons(); 100 | const expected = ['an', 'emoticon', '8D']; 101 | 102 | t.deepEquals(output, expected); 103 | t.end(); 104 | }); 105 | 106 | test('SentiText.get_words_and_emoticons removes trailing punctuation', t => { 107 | const input = 'some words!!!'; 108 | const sentiText = new SentiText(input); 109 | const output = sentiText.get_words_and_emoticons(); 110 | const expected = ['some', 'words']; 111 | 112 | t.deepEquals(output, expected); 113 | t.end(); 114 | }); 115 | 116 | test('SentiText.get_words_and_emoticons removes leading punctuation', t => { 117 | const input = '??some words'; 118 | const sentiText = new SentiText(input); 119 | const output = sentiText.get_words_and_emoticons(); 120 | const expected = ['some', 'words']; 121 | 122 | t.deepEquals(output, expected); 123 | t.end(); 124 | }); 125 | 126 | test('SentiText.get_words_and_emoticons returns empty array when input empty', t => { 127 | const input = ''; 128 | const sentiText = new SentiText(input); 129 | const output = sentiText.get_words_and_emoticons(); 130 | const expected = []; 131 | 132 | t.deepEquals(output, expected); 133 | t.end(); 134 | }); 135 | 136 | test('SentiText.get_words_and_emoticons preserves contractions', t => { 137 | const input = "this contraction don't"; 138 | const sentiText = new SentiText(input); 139 | const output = sentiText.get_words_and_emoticons(); 140 | const expected = ['this', 'contraction', "don't"]; 141 | 142 | t.deepEquals(output, expected); 143 | t.end(); 144 | }); 145 | -------------------------------------------------------------------------------- /tests/SentimentIntensityAnalyzer_tests.js: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright 2018 Comcast Cable Communications Management, LLC 3 | * Licensed under the Apache License, Version 2.0 (the "License"); 4 | * you may not use this file except in compliance with the License. 5 | * You may obtain a copy of the License at 6 | * http://www.apache.org/licenses/LICENSE-2.0 7 | * Unless required by applicable law or agreed to in writing, software 8 | * distributed under the License is distributed on an "AS IS" BASIS, 9 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 10 | * See the License for the specific language governing permissions and 11 | * limitations under the License. 12 | */ 13 | 14 | import {SentimentIntensityAnalyzer} from '../src/vaderSentiment'; 15 | let test = require('tape'); 16 | 17 | test('SentimentIntensityAnalyzer.polarity_scores match original demo output', t => { 18 | const expectedResults = [ 19 | { 20 | text: 'VADER is smart, handsome, and funny.', 21 | scores: {neg: 0.0, neu: 0.254, pos: 0.746, compound: 0.8316} 22 | }, 23 | { 24 | text: 'VADER is not smart, handsome, nor funny.', 25 | scores: {neg: 0.646, neu: 0.354, pos: 0.0, compound: -0.7424} 26 | }, 27 | { 28 | text: 'VADER is smart, handsome, and funny!', 29 | scores: {neg: 0.0, neu: 0.248, pos: 0.752, compound: 0.8439} 30 | }, 31 | { 32 | text: 'VADER is very smart, handsome, and funny.', 33 | scores: {neg: 0.0, neu: 0.299, pos: 0.701, compound: 0.8545} 34 | }, 35 | { 36 | text: 'VADER is VERY SMART, handsome, and FUNNY.', 37 | scores: {neg: 0.0, neu: 0.246, pos: 0.754, compound: 0.9227} 38 | }, 39 | { 40 | text: 'VADER is VERY SMART, handsome, and FUNNY!!!', 41 | scores: {neg: 0.0, neu: 0.233, pos: 0.767, compound: 0.9342} 42 | }, 43 | { 44 | text: 'VADER is VERY SMART, uber handsome, and FRIGGIN FUNNY!!!', 45 | scores: {neg: 0.0, neu: 0.294, pos: 0.706, compound: 0.9469} 46 | }, 47 | { 48 | text: 'The book was good.', 49 | scores: {neg: 0.0, neu: 0.508, pos: 0.492, compound: 0.4404} 50 | }, 51 | { 52 | text: 'The book was kind of good.', 53 | scores: {neg: 0.0, neu: 0.657, pos: 0.343, compound: 0.3832} 54 | }, 55 | { 56 | text: 'The plot was good, but the characters are uncompelling and the dialog is not great.', 57 | scores: {neg: 0.327, neu: 0.579, pos: 0.094, compound: -0.7042} 58 | }, 59 | { 60 | text: "At least it isn't a horrible book.", 61 | scores: {neg: 0.0, neu: 0.637, pos: 0.363, compound: 0.431} 62 | }, 63 | { 64 | text: 'Make sure you :) or :D today!', 65 | scores: {neg: 0.0, neu: 0.294, pos: 0.706, compound: 0.8633} 66 | }, 67 | { 68 | text: 'Today SUX!', 69 | scores: {neg: 0.779, neu: 0.221, pos: 0.0, compound: -0.5461} 70 | }, 71 | { 72 | text: "Today only kinda sux! But I'll get by, lol", 73 | scores: {neg: 0.179, neu: 0.569, pos: 0.251, compound: 0.2228} 74 | } 75 | ]; 76 | 77 | for (let i = 0; i < expectedResults.length; i++) { 78 | const input = expectedResults[i].text; 79 | const expectedOutput = expectedResults[i].scores; 80 | const result = SentimentIntensityAnalyzer.polarity_scores(input); 81 | t.deepEqual(result, expectedOutput, input); 82 | } 83 | 84 | t.end(); 85 | }); 86 | -------------------------------------------------------------------------------- /tests/allcap_differential_tests.js: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright 2018 Comcast Cable Communications Management, LLC 3 | * Licensed under the Apache License, Version 2.0 (the "License"); 4 | * you may not use this file except in compliance with the License. 5 | * You may obtain a copy of the License at 6 | * http://www.apache.org/licenses/LICENSE-2.0 7 | * Unless required by applicable law or agreed to in writing, software 8 | * distributed under the License is distributed on an "AS IS" BASIS, 9 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 10 | * See the License for the specific language governing permissions and 11 | * limitations under the License. 12 | */ 13 | 14 | import {allcap_differential} from '../src/vaderSentiment'; 15 | let test = require('tape'); 16 | 17 | test('allcap_differential returns false for empty array', t => { 18 | const input = []; 19 | const output = allcap_differential(input); 20 | t.equal(output, false); 21 | t.end(); 22 | }); 23 | 24 | test('allcap_differential returns false if no caps', t => { 25 | const input = ['some', 'dummy', 'words']; 26 | const output = allcap_differential(input); 27 | t.equal(output, false); 28 | t.end(); 29 | }); 30 | 31 | test('allcap_differential returns false if all caps', t => { 32 | const input = ['SOME', 'DUMMY', 'WORDS']; 33 | const output = allcap_differential(input); 34 | t.equal(output, false); 35 | t.end(); 36 | }); 37 | 38 | test('allcap_differential returns true if some caps', t => { 39 | const input = ['SOME', 'DUMMY', 'words']; 40 | const output = allcap_differential(input); 41 | t.equal(output, true); 42 | t.end(); 43 | }); 44 | -------------------------------------------------------------------------------- /tests/is_upper_python_tests.js: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright 2018 Comcast Cable Communications Management, LLC 3 | * Licensed under the Apache License, Version 2.0 (the "License"); 4 | * you may not use this file except in compliance with the License. 5 | * You may obtain a copy of the License at 6 | * http://www.apache.org/licenses/LICENSE-2.0 7 | * Unless required by applicable law or agreed to in writing, software 8 | * distributed under the License is distributed on an "AS IS" BASIS, 9 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 10 | * See the License for the specific language governing permissions and 11 | * limitations under the License. 12 | */ 13 | 14 | import {is_upper_python} from '../src/vaderSentiment'; 15 | let test = require('tape'); 16 | 17 | test('is_upper_python is false for empty string', t => { 18 | const word = ''; 19 | const result = is_upper_python(word); 20 | t.equal(result, false); 21 | t.end(); 22 | }); 23 | 24 | test('is_upper_python is true for all caps string', t => { 25 | const word = 'WORD'; 26 | const result = is_upper_python(word); 27 | t.equal(result, true); 28 | t.end(); 29 | }); 30 | 31 | test('is_upper_python is false for only special characters', t => { 32 | const word = ':)'; 33 | const result = is_upper_python(word); 34 | t.equal(result, false); 35 | t.end(); 36 | }); 37 | 38 | test('is_upper_python is true for special characters and all caps characters', t => { 39 | const word = ':)WORD:('; 40 | const result = is_upper_python(word); 41 | t.equal(result, true); 42 | t.end(); 43 | }); 44 | 45 | test('is_upper_python is false for special characters and lowercase characters', t => { 46 | const word = ':)word:('; 47 | const result = is_upper_python(word); 48 | t.equal(result, false); 49 | t.end(); 50 | }); 51 | -------------------------------------------------------------------------------- /tests/negated_tests.js: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright 2018 Comcast Cable Communications Management, LLC 3 | * Licensed under the Apache License, Version 2.0 (the "License"); 4 | * you may not use this file except in compliance with the License. 5 | * You may obtain a copy of the License at 6 | * http://www.apache.org/licenses/LICENSE-2.0 7 | * Unless required by applicable law or agreed to in writing, software 8 | * distributed under the License is distributed on an "AS IS" BASIS, 9 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 10 | * See the License for the specific language governing permissions and 11 | * limitations under the License. 12 | */ 13 | 14 | import {negated, NEGATE} from '../src/vaderSentiment'; 15 | let test = require('tape'); 16 | 17 | test('negated returns false if no input words', t => { 18 | const input_words = []; 19 | const output = negated(input_words); 20 | t.equal(output, false); 21 | t.end(); 22 | }); 23 | 24 | test('negated returns false if it contains a non negate input', t => { 25 | const input_words = ['dummy']; 26 | const output = negated(input_words); 27 | t.equal(output, false); 28 | t.end(); 29 | }); 30 | 31 | test('negated returns false if it contains multiple non negate inputs', t => { 32 | const input_words = ['dummyone', 'dummytwo', 'dummythree']; 33 | const output = negated(input_words); 34 | t.equal(output, false); 35 | t.end(); 36 | }); 37 | 38 | test('negated returns true if it contains a negate input', t => { 39 | const input_words = [NEGATE[0]]; 40 | const output = negated(input_words); 41 | t.equal(output, true); 42 | t.end(); 43 | }); 44 | 45 | test('negated returns true if it contains multiple negate inputs', t => { 46 | const input_words = ['cannot', NEGATE[0], NEGATE[1]]; 47 | const output = negated(input_words); 48 | t.equal(output, true); 49 | t.end(); 50 | }); 51 | 52 | test('negated returns true if it contains negate and non negate words', t => { 53 | const input_words = [NEGATE[0], 'dummy']; 54 | const output = negated(input_words); 55 | t.equal(output, true); 56 | t.end(); 57 | }); 58 | 59 | test("negated returns true when include_nt is true and contains a n't", t => { 60 | const input_words = ['dummyone', "somewordn't", 'dummytwo']; 61 | const output = negated(input_words); 62 | t.equal(output, true); 63 | t.end(); 64 | }); 65 | 66 | test("negated returns false when include_nt is true and doesn't contains a n't", t => { 67 | const input_words = ['dummyone', "somewordn't", 'dummytwo']; 68 | const output = negated(input_words, false); 69 | t.equal(output, false); 70 | t.end(); 71 | }); 72 | 73 | test('negated returns true if it contains least', t => { 74 | const input_words = ['dummy', 'dummy', 'least']; 75 | const output = negated(input_words); 76 | t.equal(output, true); 77 | t.end(); 78 | }); 79 | 80 | test('negated returns false if it contains least at index 0', t => { 81 | const input_words = ['least', 'dummy', 'dummy']; 82 | const output = negated(input_words); 83 | t.equal(output, false); 84 | t.end(); 85 | }); 86 | 87 | test('negated returns false if previous word is at', t => { 88 | const input_words = ['dummy', 'at', 'least']; 89 | const output = negated(input_words); 90 | t.equal(output, false); 91 | t.end(); 92 | }); 93 | -------------------------------------------------------------------------------- /tests/normalize_tests.js: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright 2018 Comcast Cable Communications Management, LLC 3 | * Licensed under the Apache License, Version 2.0 (the "License"); 4 | * you may not use this file except in compliance with the License. 5 | * You may obtain a copy of the License at 6 | * http://www.apache.org/licenses/LICENSE-2.0 7 | * Unless required by applicable law or agreed to in writing, software 8 | * distributed under the License is distributed on an "AS IS" BASIS, 9 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 10 | * See the License for the specific language governing permissions and 11 | * limitations under the License. 12 | */ 13 | 14 | import {normalize} from '../src/vaderSentiment'; 15 | let test = require('tape'); 16 | 17 | test('normalize returns score that is bounded by -1 and 1', t => { 18 | const inputs = [-1000, -100, -10, -5, -1, -0.5, 0, 0.5, 1, 5, 10, 100, 1000]; 19 | for (let i = 0; i < inputs.length; i++) { 20 | const output = normalize(inputs[i]); 21 | const lowerBounded = output >= -1.0; 22 | const upperBounded = output <= 1.0; 23 | t.equal(lowerBounded, true); 24 | t.equal(upperBounded, true); 25 | } 26 | t.end(); 27 | }); 28 | -------------------------------------------------------------------------------- /tests/scalar_inc_dec_tests.js: -------------------------------------------------------------------------------- 1 | /** 2 | * Copyright 2018 Comcast Cable Communications Management, LLC 3 | * Licensed under the Apache License, Version 2.0 (the "License"); 4 | * you may not use this file except in compliance with the License. 5 | * You may obtain a copy of the License at 6 | * http://www.apache.org/licenses/LICENSE-2.0 7 | * Unless required by applicable law or agreed to in writing, software 8 | * distributed under the License is distributed on an "AS IS" BASIS, 9 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 10 | * See the License for the specific language governing permissions and 11 | * limitations under the License. 12 | */ 13 | 14 | import {scalar_inc_dec, BOOSTER_DICT, C_INCR} from '../src/vaderSentiment'; 15 | let test = require('tape'); 16 | 17 | test('scalar_inc_dec returns 0 if word is not a booster word', t => { 18 | const input = 'xxnotawordxx'; 19 | const output = scalar_inc_dec(input, 1, false); 20 | t.equal(output, 0); 21 | t.end(); 22 | }); 23 | 24 | test('scalar_inc_dec returns BOOSTER_DICT val if word is a booster word', t => { 25 | const keys = Object.keys(BOOSTER_DICT); 26 | const key = keys[0]; 27 | const output = scalar_inc_dec(key, 1, false); 28 | const expected = BOOSTER_DICT[key]; 29 | t.equal(output, expected); 30 | t.end(); 31 | }); 32 | 33 | test('scalar_inc_dec increments scalar if is_cap_diff is true', t => { 34 | const keys = Object.keys(BOOSTER_DICT); 35 | const key = keys[0]; 36 | const input = key.toUpperCase(); 37 | const output = scalar_inc_dec(input, 1, true); 38 | const expected = BOOSTER_DICT[key] + C_INCR; 39 | t.equal(output, expected); 40 | t.end(); 41 | }); 42 | -------------------------------------------------------------------------------- /webpack.config.js: -------------------------------------------------------------------------------- 1 | var path = require('path'); 2 | var webpack = require('webpack'); 3 | module.exports = { 4 | entry: './src/index.js', 5 | output: { 6 | path: path.resolve(__dirname, 'build'), 7 | filename: 'vaderSentiment.bundle.js', 8 | library: 'SentimentIntensityAnalyzer', 9 | libraryTarget: 'commonjs', 10 | libraryExport: 'default' 11 | }, 12 | module: { 13 | rules: [ 14 | { 15 | use: { 16 | loader:'babel-loader', 17 | options: { presets: ['es2015'] } 18 | }, 19 | test: /\.js$/, 20 | exclude: /node_modules/ 21 | } 22 | ] 23 | }, 24 | mode: 'production' 25 | }; 26 | --------------------------------------------------------------------------------