Now computers can sense anger from more than furious button mashing
Computer eggheads from Italy's University of Bari have developed what they claim is "the first open-source toolkit for emotion recognition from text."
Developers of Twitter bots, among others, often employ sentiment analysis to evaluate whether text expresses positive or negative feelings.
Google engineer Max Braun, for example, earlier this year released code for a bot designed to buy and sell the stock of public companies mentioned in President Trump's tweets, based on the sometimes correct premise that Trump's praise or condemnation will move the stock price.
To understand Trump's tweets, the code relies on Google's Cloud Natural Language API, which ingests text and returns a variety of data about it.
In addition to identifying people, organizations, products, events, and places, Google's API provides a score ranging from -1.0 (negative) to 1.0 (positive).