sentimentAnalysis   611

« earlier    

vmarkovtsev/BiDiSentiment: Two-way deep RNN for sentiment classification.
GitHub is where people build software. More than 27 million people use GitHub to discover, fork, and contribute to over 80 million projects.
python  rnn  sentimentanalysis 
11 days ago by geetarista
Search | Stephen F. Austin - Digital Collection
Search by keyword, author, recipient, date range, locations, and sentiment scores (rankings of the positivity or negativity of the letters). View your results as a document list, a timeline plotted by sentiment scores, a map of the letters’ geography, and ranked word counts.
infovis  Dataviz  sentimentanalysis  textmining  text 
5 weeks ago by miaridge
About | Stephen F. Austin - Digital Collection
After experimenting with six different open-source ruby sentiment analysis libraries from GitHub, DAP settled on the open-source TextMood. Each document in the collection was run against the program’s dictionary and given a sentiment score based on the cumulative positive and negative weight of the words within that document.

We used three approaches to check the quality of the results after applying sentiment analysis to the DAP corpus.
sentimentanalysis  textmining  tdm  DigitalHumanities  DigitalHistory 
5 weeks ago by miaridge
How social media reflects our daily mood changes
How social media reflects our daily mood changes Sad in the morning, angry by evening. Sigh.
moodtech  socialmedia  emotion  emotionanalytics  sentimentanalysis 
11 weeks ago by Ssivek
[1704.01444] Learning to Generate Reviews and Discovering Sentiment
We explore the properties of byte-level recurrent language models. When given sufficient amounts of capacity, training data, and compute time, the representations learned by these models include disentangled features corresponding to high-level concepts. Specifically, we find a single unit which performs sentiment analysis. These representations, learned in an unsupervised manner, achieve state of the art on the binary subset of the Stanford Sentiment Treebank. They are also very data efficient. When using only a handful of labeled examples, our approach matches the performance of strong baselines trained on full datasets. We also demonstrate the sentiment unit has a direct influence on the generative process of the model. Simply fixing its value to be positive or negative generates samples with the corresponding positive or negative sentiment.
december 2017 by hustwj

« earlier    

related tags

2016  adweek  ai  akka  algorithmicbias  algorithmics  analysis  api  apis  artificialintelligence  aws  azure  badstats  beautiful  bias  bigdata  books  brexit  campaigning  chatbot  classification  cloud  code  corpora  counterclaim  courses  creativeshowcase  cx  data-analysis  data  dataanalysis  datacreation  dataenrichment  datamining  datascience  dataviz  dc:creator=davieswill  dctagged  deeplearning  development  di  digitalhistory  digitalhumanities  discourse  dj  dove  education  emotion  emotionanalytics  emotions  enrichment  entityextraction  evilness  experiment  expression  facialrecognition  fakenews  fb  fmcg  google  happiness  happy  homophobia  howto  images  infovis  ipython  janeausten  kafka  kanyewest  keras  language  lda  learning  lies  location  lstm  machine-learning  machine  machinecomprehension  machinelearning  microsite  microsoft  misinformation  misogyny  ml  moodtech  music  n;p  narrative  ner  neuralnetwork  news  nlp  nltk  onlineadvertising  opinionmining  package  pdf  personalisation  playframework  politics  populism  programming  psychology  python  r-language  r-project  r  racism  reddit  research  rnn  rstats  ruby  s  scary  semantic  sentiment-analysis  sentiment  sentimentanalysis  slides  smm  social  socialmedia  society  spark  startups  statistics  tdm  teaching  technology  tensorflow  text-analysis  text-mining  text  text_classification  textanalysis  textblob  textmining  tools  translation  trends  trump  trumpdonald  truth  tutorial  tweetit  twitter  video  vis  visualisation  visualization  washpo  webscraping  word2vec  wordembedding  wordembeddings  worstpractice 

Copy this bookmark: