It uses so-called "sentiment analysis" software to assess text.
Using a string of individually addressable RGB LEDs and sentiment analysis software from Stanford University.
Our experimental analysis of classification tasks, including sentiment analysis, software defect prediction, credit risk modeling, spam filtering, and semantic mapping, suggests that the proposed classification scheme can predict better than conventional ensemble learning methods such as AdaBoost, bagging, random subspace, and majority voting.
For example, a person who exhibits curiosity by visiting many Islamist websites and asking numerous questions in online forums might be flagged by sentiment-analysis software if he shows signs of resentment and eventually turns to "radicalising" others by, say, justifying violence and providing links to militant videos.
Using today's AI techniques like sentiment analysis — in which software can understand language and extract how the writer feels about a topic — can allow airlines to assess what tens of thousands of customers are feeling about their services by looking at their tweets.
While taking Politics in Iran, Cameron Ramos wrote a sentiment analysis program and scraped software to analyze trends between the Twitter feeds of Iranian government officials, the country's elections, and the Iran nuclear deal.
Equally important, such software allows sentiment analysis, which would take weeks to do manually, to be carried out in real-time and on an 11-point scale instead of the basic threal-time andt (ponitive, neutran or negative).
Tweets were grouped into sequential monthly time periods for sentiment analysis using the twitteR R package (https://github.com/geoffjentry/twitteR/) and Jeffrey Breen's sentiment analysis code (https://github.com/jeffreybreen/twitter-sentiment-analysis-tutorial-201107; a tutorial can be found at: http://www.inside-r.org/howto/mining-twitter-airline-consumer-sentiment).
Appian allows users to create software application user interfaces with AI-based sentiment analysis to inform and improve human decision making.
Many topics beyond product reviews like stock markets, elections, disasters, medicine, software engineering and cyberbullying extend the utilization of sentiment analysis.
Sentiment analysis of viewers' comments on Invisalign was carried out using SentiStrength software (version 2.2, copyright Professor M. Thelwall, Faculty of Science and Engineering, University of Wolverhampton, UK), a sentiment analysis tool widely applied to sentiment detection on social network sites [15 19].
