Emotional Divergence Influences Information Spreading in Twitter

Pfitzner, Rene (ETH Zurich) | Garas, Antonios (ETH Zurich) | Schweitzer, Frank (ETH Zurich)

AAAI Conferences 

We analyze data about the micro-blogging site Twitter using sentiment extraction techniques. From an information perspective, Twitter users are involved mostly in two processes: information creation and subsequent distribution (tweeting), and pure information distribution (retweeting), with pronounced preference to the first. However a rather substantial fraction of tweets are retweeted. Here, we address the role of the sentiment expressed in tweets for their potential aftermath. We find that although the overall sentiment (polarity) does not influence the probability of a tweet to be retweeted, a new measure called "emotional divergence" does have an impact. In general, tweets with high emotional diversity have a better chance of being retweeted, hence influencing the distribution of information.

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