stream.on('data', function(tweet) {
var result = sentiment(tweet.text);
console.log('[' + result.score + ']', tweet.text);
});
s_afinn = user.tweets.reduce(function (acc, tweet) {
tweet.sentiment_afinn = sentiment(tweet.text).score;
return (acc + tweet.sentiment_afinn);
}, 0) / user.tweets.length;
router.get('/analyze', function (req, res, next) {
var tweet = decodeURIComponent(req.query.tweet);
var analyzed = sentiment(tweet);
res.status(200).send(analyzed);
});
/**
* Renders display-only data for a match
**/
function renderMatch(m) {
//do render-only processing (not needed for aggregation, only for match display)
m.players.forEach(function(p, i) {
//converts hashes to arrays and sorts them
var targets = ["ability_uses", "item_uses", "damage_inflictor"];
targets.forEach(function(target) {
if (p[target]) {
var t = [];
for (var key in p[target]) {
var a = constants.abilities[key];
var i = constants.items[key];
var def = {
img: "/public/images/default_attack.png"
};
def = a || i || def;
var result = {
img: def.img,
name: key === "undefined" ? "Auto Attack/Other" : key,
val: p[target][key],
className: a ? "ability" : i ? "item" : "img-sm"
};
if (p.hero_hits) {
result.hero_hits = p.hero_hits[key];
}
t.push(result);
}
t.sort(function(a, b) {
return b.val - a.val;
});
p[target + "_arr"] = t;
}
});
//filter interval data to only be >= 0
if (p.times) {
var intervals = ["lh_t", "gold_t", "xp_t", "times"];
intervals.forEach(function(key) {
p[key] = p[key].filter(function(el, i) {
return p.times[i] >= 0;
});
});
}
});
if (m.chat) {
//make a list of messages and join them all together for sentiment analysis
var chat_words = m.chat.map(function(message) {
return message.key;
}).join(' ');
m.sentiment = sentiment(chat_words, {
"report": -2,
"commend": 2,
"noob": -2,
"ff": -1,
"bg": -1,
"feed": -1,
"ty": 1,
"thanks": 1,
"wp": 1,
"end": -1,
"garbage": -1,
"trash": -1,
"throw": -1,
"salt": -1,
"ez": -1,
"mad": -1
});
}
//create gold breakdown data
if (m.players[0].gold_reasons) {
m.incomeData = generateIncomeData(m);
m.treeMapData = generateTreemapData(m);
}
//create graph data
if (m.players[0].gold_t) {
m.graphData = generateGraphData(m);
}
//create heatmap data
m.posData = m.players.map(function(p) {
return p.posData;
});
//process objectives
if (m.objectives) {
m.objectives.forEach(function(entry) {
entry.objective = constants.objectives[entry.subtype] || entry.subtype;
var p = m.players[entry.slot];
if (p) {
entry.team = entry.team === 2 || entry.key < 64 || p.isRadiant ? 0 : 1;
entry.hero_img = constants.heroes[p.hero_id] ? constants.heroes[p.hero_id].img : "";
}
});
}
//process teamfight data
if (m.teamfights) {
m.teamfights.forEach(function(tf) {
tf.posData = [];
tf.radiant_gold_delta = 0;
tf.radiant_xp_delta = 0;
tf.radiant_participation = 0;
tf.radiant_deaths = 0;
tf.dire_participation = 0;
tf.dire_deaths = 0;
tf.players.forEach(function(p) {
//lookup starting, ending level
p.level_start = getLevelFromXp(p.xp_start);
p.level_end = getLevelFromXp(p.xp_end);
function getLevelFromXp(xp) {
for (var i = 0; i < constants.xp_level.length; i++) {
if (constants.xp_level[i] > xp) {
return i;
}
}
return constants.xp_level.length;
}
});
//add player's hero_id to each teamfight participant
m.players.forEach(function(p, i) {
var tfplayer = tf.players[p.player_slot % (128 - 5)];
tfplayer.hero_id = p.hero_id;
tfplayer.player_slot = p.player_slot;
tfplayer.isRadiant = isRadiant(p);
tfplayer.personaname = p.personaname;
tfplayer.account_id = p.account_id;
tfplayer.participate = tfplayer.deaths > 0 || tfplayer.damage > 0;
if (!p.teamfights_participated) {
p.teamfights_participated = 0;
}
p.teamfights_participated += tfplayer.participate ? 1 : 0;
//compute team gold/xp deltas
if (isRadiant(p)) {
tf.radiant_gold_delta += tfplayer.gold_delta;
tf.radiant_xp_delta += tfplayer.xp_delta;
tf.radiant_participation += tfplayer.participate ? 1 : 0;
tf.radiant_deaths += tfplayer.deaths ? 1 : 0;
}
else {
tf.radiant_gold_delta -= tfplayer.gold_delta;
tf.radiant_xp_delta -= tfplayer.xp_delta;
tf.dire_participation += tfplayer.participate ? 1 : 0;
tf.dire_deaths += tfplayer.deaths ? 1 : 0;
}
//convert 2d hash to array
tfplayer.posData = generatePositionData({
deaths_pos: 1
}, tfplayer);
//console.log(player);
//add player hero id to each death, push into teamfight death position array
tfplayer.posData.deaths_pos.forEach(function(pt) {
pt.hero_id = tfplayer.hero_id;
tf.posData.push(pt);
});
});
});
}
}
stream.on('data', function(data) {
console.log(data);
var text = data.text;
var sentimentResult = sentiment(text);
console.log(sentimentResult);
});
async.each(workers, function(item, callback) {
// Check if the worker has timed out (Every worker has a 48hour lifetime)
if (item.validateTimeout() === true) {
// Emit the new status (Worker timed out)
io.sockets. in (item.id).emit('statusChanged', storage.getWorkerById(item.id).getStatus());
// Delete the worker
storage.deleteWorker(item.id);
// Delete the job
Job
.findOne({
_id: item.id
})
.exec(function(err, job) {
if (err) console.log(err);
if (!job) console.log(new Error('Failed to find Job ' + item.id));
// Remove the job
job.remove(function(err) {
if (err) console.log(err);
console.log(new Date() + " Job " + item.id + " was delete because of timeout!");
});
});
return false;
}
// Check if the worker is active
if (item.active === true) {
// Check if the worker timer has not expired
if (item.validateTimer()) {
// Check for the right location
if(item.checkLocation(tweet) === false) {
return false;
}
// Check if the tweet contains any keyword
if(item.checkKeywords(tweet.text) === false) {
return false;
}
// Analyse the tweet
senti(tweet.text, function(err, result) {
// Let the worker calculate the results
item.analyse(result, function(data) {
// Emit the statistics to the user
io.sockets. in (item.id).emit('statistics', data);
});
// Add the sentiment result to the tweet object
tweet.sentiment = result;
// Store the new tweet in the active worker
item.pushData(tweet);
// Emit the new tweet to the user
io.sockets. in (item.id).emit('tweet', tweet);
});
// Worker has finished
} else {
// Emit the new status (Worker finished)
io.sockets. in (item.workerId).emit('statusChanged', item.getStatus());
// Delete the worker
storage.deleteWorker(item.id);
// Find and save the job
Job
.findOne({
_id: item.id
})
.exec(function(err, job) {
if (err) console.log(err);
if (!job) console.log(new Error('Failed to find Job ' + item.id));
// Update the job
job.status = item.getStatus();
job.filterData = item.getFilterData();
job.streamData = item.getStreamData();
job.sentimentData = item.getSentimentData();
job.timer = item.getTimer();
job.save(function(err) {
if (err) console.log(err);
console.log(new Date() + " Job " + item.id + " was saved");
});
});
}
}
callback();
}, function(err) {
stream.on(channel, function(tweet) {
cache[tag].total++;
cache[tag].sentiment += sentiment(tweet.text).score;
console.log(tweet.text);
});
let sentimentnorm = _.mean(_.map(group, post => {
let sent = Sentiment(post.raw);
let num = sent.positive + sent.negative;
if (num == 0) return 0;
return sent.score / (num);
}));
const analyze = (textObject, queryString) => {
//console.log("MEE",textObject)
queryString = Array.isArray(queryString)?queryString[0]:queryString;
topics={};
let rankingHolder = [];
let negativeSentiments = 0;
let positiveSentiments = 0;
let maxSentimentImpact = {actualTweet:'', sentimentStrength:0, votes:0, posNeg:""};
for (var postKey in textObject) {
let curr = textObject[postKey];
let content = curr.content;
for (var contentKey in content) {
//console.log(content[contentKey].text)
nlpAnalysis(content[contentKey].text);
let currentSentiment = sentiment(content[contentKey].text);
if (currentSentiment.positive.length != 0 || currentSentiment.negative.length != 0) {
content[contentKey].sentiment = currentSentiment;
if(currentSentiment.score<0)
negativeSentiments++
if(currentSentiment.score>0)
positiveSentiments++
content[contentKey].sentiment.w_rank = ranking(content[contentKey], textObject[postKey].author);
let rankProp = content[contentKey].sentiment.w_rank[1];
if(maxSentimentImpact.sentimentStrength <rankProp){
maxSentimentImpact.sentimentStrength = content[contentKey].sentiment.w_rank[0];
maxSentimentImpact.actualTweet = content[contentKey].text;
maxSentimentImpact.votes = content[contentKey].vote_count;
maxSentimentImpact.posNeg = content[contentKey].sentiment<0?"Negative":"Positive"
}
rankingHolder.push(content[contentKey].sentiment.w_rank);
}else{
delete textObject[postKey].content;
}
}
}
//console.log(JSON.stringify(textObject))
let normalData = normal_dist_data_filter(rankingHolder);
negativeSentiments = negativeSentiments/rankingHolder.length
positiveSentiments = positiveSentiments/rankingHolder.length
normalData.percentPositive = positiveSentiments;
normalData.percentNegative = negativeSentiments;
let greater = normalData.mean + (2*normalData.standardDeviation);
//console.log(normalData)
let less = normalData.mean - (2*normalData.standardDeviation);
normalData.set = normalData.set.filter(function(curr){
return curr[0]<greater && curr[0]>less;
});
let data_W_analysis = {
data: textObject
}
//extendOn(data_W_analysis, [normalData,maxSentimentImpact]);
var sortable = [];
for (var key in topics){ //TODO FIX FILTERING, IM JUST RUSHING
if( key.trim().indexOf(" ")==-1&&key.trim().indexOf("'")==-1&&key.trim().indexOf(".")==-1&&key.trim().indexOf("@")==-1)
sortable.push([key, topics[key]])
}
sortable = sortable.sort(
function(a, b) {
return b[1] - a[1];
}
).slice(1,7);
//console.log("HERE",sortable.slice(0,20));
for (let dataKey in normalData) {
data_W_analysis[dataKey] = normalData[dataKey]
}
for (let dataKey in maxSentimentImpact) {
data_W_analysis[dataKey] = maxSentimentImpact[dataKey]
}
var trendingFiltered = [];
for(var key in sortable){
if(sortable[key][0].trim().toLowerCase().indexOf(queryString.trim().toLowerCase())==-1)
trendingFiltered.push(sortable[key]);
}
data_W_analysis.trendingTopics = trendingFiltered;
data_W_analysis.query = queryString;
//console.log("DONE",data_W_analysis)
//console.log("FINAL RETURN", trendingFiltered)
return data_W_analysis;
};
/**
* Tally up the votes on a PR, and monitor which users are stargazers.
*/
function tallyVotes(pr) {
var tally = pr.comments.reduce(function (result, comment) {
var user = comment.user.login,
body = comment.body;
// Don't check comments from the config user.
if (user === config.user) return result;
// People that don't star the repo cannot vote.
if (!cachedStarGazers[user]) {
result.nonStarGazers.push(user);
return result;
}
// Skip people who vote both ways.
var voteCast = calculateUserVote(body);
if (voteCast === null) {
return result;
}
result.votes[user] = voteCast;
return result;
}, {
votes: {},
nonStarGazers: [],
});
// Add the PR author as a positive vote.
tally.votes[pr.user.login] = true;
// determine whether I like this PR or not (or don't care)
var score = sentiment(pr.title + ' ' + pr.body).score;
if (score > 1) {
tally.votes[config.user] = true;
} else if (score < -1) {
tally.votes[config.user] = false;
}
var tallySpread = Object.keys(tally.votes).reduce(function (result, user) {
// Increment the positive/negative counters.
if (tally.votes[user]) {
result.positive++;
} else {
result.negative++;
}
result.total++;
return result;
}, {
positive: 0,
negative: 0,
total: 0
});
tallySpread.percentPositive = percent(tallySpread.positive / tallySpread.total);
tallySpread.percentNegative = percent(tallySpread.negative / tallySpread.total);
_.merge(tally, tallySpread);
// Store this so that we can eventually make a votes webserver endpoint.
votesPerPR[pr.number] = tally;
return tally;
}
var saveTweet = function(tag, tweet){
var sentimentData = sentiment(tweet.text);
if(sentimentData.score !== 0 ) {
twitterModels.Tweet.create({ tweet: tweet.text, sentiment: sentimentData.score, tag: tag});
}
};
response.on('end', function() {
var allArticles = '';
var responseFull = JSON.parse(body);
var articles = responseFull.response.results.length;
for (var i = articles - 1; i >= 0; i--) {
var sentence = responseFull.response.results[i].fields.body; // get text
//console.log(sentence);
var stripped = sentence.replace(/(<([^>]+)>)/g,""); // strip html
allArticles += stripped;
};
var analysed = sentiment(allArticles);
Mood.findOne(4).done(function(err, item) {
// Error handling
if (err) {
return console.log(err);
// The item was found successfully!
} else {
item.value = parseInt(item.value) + 1; // add sentiment to news total
item.save(function (err) {
if (err) return res.send(err,500);
// Report back with the new state of the item
Mood.publishUpdate( 4, {
value: parseInt(item.value)
});
});
}
});
fs.writeFile(today, JSON.stringify({
numberwang: analysed.score,
comparative: analysed.comparative,
'analysed articles': articles,
date: date,
'positive words total': analysed.positive.length,
'negative words total': analysed.negative.length
// ,
// positive: analysed.positive,
// negative: analysed.negative,
// body: responseFull
}), function(err) {
if(err) {
console.log(err);
} else {
console.log(today +" was saved.");
}
});
return res.send({
numberwang: analysed.score,
comparative: analysed.comparative,
'analysed articles': articles,
'positive words total': analysed.positive.length,
'negative words total': analysed.negative.length,
// positive: analysed.positive,
// negative: analysed.negative
})
});
export default (state) => {
const sentence = sentiment(state.sentence.toLowerCase());
state.sentiment = sentence.score;
return(state);
};
let sentiment = _.map(group, post => {
let sent = Sentiment(post.raw);
return sent.score;
});
strings.forEach((string) => {
sentences.push({
string: string,
sentiment: sentiment(string)
});
});
let sentimentcomp = _.map(group, post => {
let sent = Sentiment(post.raw);
return sent.comparative;
});
stream.on('tweet', function(tweet) {
let individualSent = sentiment(tweet.text)
if (individualSent.score > 0) {
pos++
} else if (individualSent.score < 0) {
neg++
} else if (individualSent.score === 0) {
neu++
}
if (individualSent.score > 0) {
scoreArray.push(individualSent.score)
} else if (individualSent.score < 0) {
scoreArray.push(individualSent.score * 1.35)
}
// push tweets to array
streamedTweets.push(tweet.text)
//Tweet location
// if tweet has cooridnates
if(tweet.coordinates) {
//and if coordiantes don't = null
if(tweet.coordinates != null) {
//get location sentiment and lng / lat
let outputPoint = {"lat": tweet.coordinates.coordinates[0],"lng": tweet.coordinates.coordinates[1]};
let locSentiment = sentiment(tweet.text)
// push to the location array
tweetsWithLoc.push({"tweet": tweet.text, "location": outputPoint, "sentiment": locSentiment});
}
}
// When there are 40 tweets push to client
if(tweetsWithLoc.length === 80) {
try {
wss.clients.forEach(function each(client) {
if (client.readyState === WebSocket.OPEN) {
client.send(JSON.stringify({"location":tweetsWithLoc}));
}
});
} catch(e) {
console.log(e)
}
// resset array
tweetsWithLoc.length = 0;
}
//send streamed tweets off when the array hits 50 tweets
if(streamedTweets.length === 50) {
scoreArrayLength = scoreArray.length
average = scoreArray.reduce((a, b) => a + b, 0);
average = average / scoreArrayLength;
average = average.toFixed(4);
average = parseFloat(average)
//join all the tweets in the array to a single string
let trumpSentiment = sentiment(streamedTweets.join());
let words = countThem(trumpSentiment.tokens)
// FIRE!!
try {
wss.clients.forEach(function each(client) {
if (client.readyState === WebSocket.OPEN) {
client.send(JSON.stringify({"main": {"sentiment": trumpSentiment, "featuredTweet": streamedTweets[19], "pos": pos, "neg": neg, "neu": neu, "average": average, "words":words}}))
}
});
} catch(e) {
console.log(e)
}
//clear array & start over
scoreArrayLength = 0;
scoreArray.length = 0;
streamedTweets.length = 0;
pos = 0
neg = 0
neu = 0
}
})
const sentiments = tweetStream.map((tweet) => {
return sentiment(tweet.text);
});
getSentiment(text){
var score = sentiment(text).score;
return Math.tanh(score);
}
function score(sentence, callback){
var value = Mood(sentence);
//console.log(value.score);
var score = value.score;
callback(score);
}
$('.ProfileTweet-text').toArray().forEach(function(item) {
var text = $(item).text();
var results = sentiment(text);
console.log(sentimentToSmiley(results), '-', text.replace(/\n/g, ' '));
});
var sentiments = messages.map(function(message){
return { message: message, score: analyzeSentiment(message).score };
})
fs.readFile('books/alice_scrubbed', 'utf-8', (err, data) => {
if (err) throw err;
textArray = data.split('.');
for (i =0; i < 3; i++) {
var blah = '';
var blah2 = '';
var blah3 = '';
//console.log(sentiment(textArray[i]))
score[i] = sentiment(textArray[i]).score;
alchemy.sentiment(textArray[i], {}, function(err, response) {
if (err) throw err;
// See http://www.alchemyapi.com/api/ for format of returned object
alchemySentiment = response.docSentiment;
console.log(JSON.stringify(alchemySentiment));
// Do something with data
alchemyScore.push( JSON.stringify(alchemySentiment));
})
if (score[i] % 7 === 0) {
blah += 'c';
} else if (score[i] % 7 == 1 || score[i] % 7 == -1) {
blah += 'd';
} else if (score[i] % 7 == 2 || score[i] % 7 == -2) {
blah += 'e';
} else if (score[i] % 7 == 3 || score[i] % 7 == -3) {
blah += 'f';
} else if (score[i] % 7 == 4 || score[i] % 7 == -4) {
blah += 'g';
} else if (score[i] % 7 == 5 || score[i] % 7 == -5) {
blah += 'a';
} else if (score[i] % 7 == 6 || score[i] % 7 == -6) {
blah += 'b';
} else {
console.log('wut');
}
if (score[i] < -5) {
blah2 = blah + 4;
blah3 = blah + 6;
blah += 2;
} else if (score[i] < -4) {
blah2 = blah + 4;
blah3 = blah + 6;
blah += 2;
} else if (score[i] < -3) {
blah2 = blah + 4;
blah3 = blah + 6;
blah += 2;
} else if (score[i] < -2) {
blah2 = blah + 4;
blah3 = blah + 6;
blah += 2;
} else if (score[i] < -1) {
blah2 = blah + 4;
blah3 = blah + 6;
blah += 2;
} else if (score[i] < 0) {
blah2 = blah + 4;
blah3 = blah + 6;
blah += 2;
} else if (score[i] < 1) {
blah2 = blah + 4;
blah3 = blah + 6;
blah += 2;
} else if (score[i] < 2) {
blah2 = blah + 4;
blah3 = blah + 6;
blah += 2;
} else if (score[i] < 3) {
blah2 = blah + 4;
blah3 = blah + 6;
blah += 2;
} else if (score[i] < 4) {
blah2 = blah + 4;
blah3 = blah + 6;
blah += 2;
} else {
blah2 = blah + 4;
blah3 = blah + 6;
blah += 2;
}
chord = [blah, blah2, blah3];
music.push(chord);
}
for (var j = 0; j < music.length; j++ ) {
track.note(0, music[j][0], 64);
track.noteOn(0, music[j][1]);
track.noteOn(0, music[j][2]);
}
fs.writeFileSync('test.mid', file.toBytes(), 'binary');
});