Prediction of emotional reaction of social media users to news articles
What is it about?
Social networks users express emotions in their post as a reaction to news articles. By using a supervised algorithm, we proposed a method to predict the distribution of the emotions that users will express as a reaction to news articles.
Why is it important?
Emotion detection has been mostly studied from the writer's perspective where the content of a post is used to determine the sentiment polarity or emotions expressed on it. On the other hand, there has been less efforts in detecting the emotion from the reader’s perspective, where the content of a post is used to determine the sentiment polarity or emotions that this post would generate on readers. In addition to that, to our knowledge the use of a multi-target strategy to predict multiple emotions has not been used before.