A Collection for Detecting Triggers of Sentiment Spikes

Anastasia Giachanou, Ida Mele, Fabio Crestani

Abstract: The advent of social media has given the opportunity to users to publicly express and share their opinion about any topic. Public opinion is very important for the interested entities that can leverage such information in the process of making decisions. In addition, identifying sentiment changes and the likely causes that have triggered them allows interested parties to adjust their strategies and attract more positive sentiment. With the aim to facilitate research on this problem, we describe a collection of tweets that can be used for detecting and ranking the likely triggers of sentiment spikes towards different entities. To build the collection, we first group tweets by topic which are then manually annotated according to sentiment polarity and strength. We believe that this collection can be useful for further research on detecting sentiment change triggers, sentiment analysis and sentiment prediction.