Microblogging and social news web sites like Twitter are largely used as an important source of up-to-date information. Consequently, organizations and firms have interest in using those platforms to diffuse their own news and updates. The dynamics of information or rumor spread in online social networks depends mainly on network characteristics and is currently a critical topic in Social Network Analysis (SNA). The diffusion through' retweets' of such information occurs in a time lapse immediately after the publication of the original tweet, and it is internal to some hashtag-based' channel'. In this study, the retweet count of a given tweet is assumed as an index of its diffusion. For analyzing the statistical features of viral tweets, we have selected five tweets. Our model is based on the hypothesis that it is highly probable that a user decides to retweet a tweet if he/she is following either the tweet author, or another retweeter of the tweet. Therefore, we choose as main features of a tweet its number of retweets and the number of followers of retweeting users.

Estimating the spreading of viral threads on twitter / Corvacchiola, Luigi; Iotti, Eleonora; Tomaiuolo, Michele. - 1959:(2017). ((Intervento presentato al convegno 3rd International Workshop on Knowledge Discovery on the WEB, KDWEB 2017 tenutosi a ita nel 2017.

Estimating the spreading of viral threads on twitter

CORVACCHIOLA, LUIGI;Iotti, Eleonora;Tomaiuolo, Michele
2017

Abstract

Microblogging and social news web sites like Twitter are largely used as an important source of up-to-date information. Consequently, organizations and firms have interest in using those platforms to diffuse their own news and updates. The dynamics of information or rumor spread in online social networks depends mainly on network characteristics and is currently a critical topic in Social Network Analysis (SNA). The diffusion through' retweets' of such information occurs in a time lapse immediately after the publication of the original tweet, and it is internal to some hashtag-based' channel'. In this study, the retweet count of a given tweet is assumed as an index of its diffusion. For analyzing the statistical features of viral tweets, we have selected five tweets. Our model is based on the hypothesis that it is highly probable that a user decides to retweet a tweet if he/she is following either the tweet author, or another retweeter of the tweet. Therefore, we choose as main features of a tweet its number of retweets and the number of followers of retweeting users.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11381/2841786
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