|Title||A probabilistic author-centered model for Twitter discussions|
|Publication Type||Conference Paper|
|Year of Publication||2018|
|Authors||Alsinet T, Argerlich J., Bejar R, Esteva F, Godo L|
|Conference Name||IPMU 2018|
In a recent work some of the authors have developed an argumenta- tive approach for discovering relevant opinions in Twitter discussions with prob- abilistic valued relationships. Given a Twitter discussion, the system builds an argument graph where each node denotes a tweet and each edge denotes a crit- icism relationship between a pair of tweets of the discussion. Relationships be- tween tweets are associated with a probability value, indicating the uncertainty on whether they actually hold. In this work we introduce and investigate a natural extension of the representation model, referred as probabilistic author-centered model. In this model, tweets by a same author are grouped, describing his/her opinion in the discussion, and are represented with a single node in the graph, while edges stand for criticism relationships or controversies between opinions of Twitter users in the discussion. In this new model, interactions between authors can give rise to circular criticism relationships, and the probability of one opin- ion criticizing another are evaluated from the probabilities of criticism among the individual tweets that compose both opinions.
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