Tweet Sentiment Analysis with Pronoun Choice Reveals Online Community Dynamics in Response to Crisis Events

  • Shaikh Samira
  • Feldman Laurie Beth
  • Barach Eliza
  • Marzouki Yousri

  • Human factors
  • Sentiment analysis
  • Social media
  • Natural language
  • Big data


We describe the emergence of an online community from naturally occurring social media data. Our method uses patterns of word choice in an online social platform to characterize how a community forms in response to adverse events such as a terrorist attack. Our focus is English Twitter messages after the Charlie Hebdo terrorist attack in Paris in January 2015). We examined the text to find lexical variation associated with measures of valence, arousal and concreteness. We also examine the patterns of language use of the most prolific twitter users (top 2 % by number of tweets) and the most frequent tweets in our collection (top 2 % by number of retweets). Differences between users and tweets based on frequency are revealing about how lexical variation in tweeting behavior reflects evolution of a community in reaction to crisis events on an international scale.