sentimentAnalysis   608

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Browsing Histories – SHARE LAB
This story was based on just a tiny excerpt, a two-hour sample, from the internet browsing history of a Swiss journalist J. B. In late June 2015 he visited the Tactical Tech office in Berlin as he was assigned to lay open his private life and see what can be told from the data he creates on his devices.
A year later, we gathered in Berlin for a week of data investigations and one of the data sets that we explored was the browsing history collection of Mr. J. Our goal was to find out how much we could learn from someone’s browsing history or, to rephrase it, what others can learn by exploiting data from our own browsing history.
dj  Privacy  browser  browsinghistory  Networkanalysis  cookies  sentimentanalysis  ai  nlg  surveillance 
19 hours ago by paulbradshaw
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 
10 weeks 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 
february 2018 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 
february 2018 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 
january 2018 by Ssivek

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