TY - GEN
T1 - Retweetability analysis and prediction during Hurricane sandy
AU - Neppalli, Venkata K.
AU - Medeiros, Murilo Cerqueira
AU - Caragea, Cornelia
AU - Caragea, Doina
AU - Tapia, Andrea H.
AU - Halse, Shane
PY - 2016
Y1 - 2016
N2 - Twitter is a very important source for obtaining information, especially during events such as natural disasters. Users can spread information in Twitter either by crafting new posts, which are called "tweets," or by using retweet mechanism to re-post the previously created tweets. During natural disasters, identifying how likely a tweet is to be highly retweeted is very important since it can help promote the spread of good information in a network such as Twitter, as well as it can help stop the spread of misinformation, when corroborated with approaches that identify trustworthy information or misinformation, respectively. In this paper, we present an analysis on retweeted tweets to determine several aspects affecting retweetability. We then extract features from tweets' content and user account information and perform experiments to develop models that automatically predict the retweetability of a tweet in the context of the Hurricane Sandy.
AB - Twitter is a very important source for obtaining information, especially during events such as natural disasters. Users can spread information in Twitter either by crafting new posts, which are called "tweets," or by using retweet mechanism to re-post the previously created tweets. During natural disasters, identifying how likely a tweet is to be highly retweeted is very important since it can help promote the spread of good information in a network such as Twitter, as well as it can help stop the spread of misinformation, when corroborated with approaches that identify trustworthy information or misinformation, respectively. In this paper, we present an analysis on retweeted tweets to determine several aspects affecting retweetability. We then extract features from tweets' content and user account information and perform experiments to develop models that automatically predict the retweetability of a tweet in the context of the Hurricane Sandy.
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M3 - Conference contribution
AN - SCOPUS:85015746089
T3 - Proceedings of the International ISCRAM Conference
BT - ISCRAM 2016 Conference Proceedings - 13th International Conference on Information Systems for Crisis Response and Management
A2 - Antunes, Pedro
A2 - Banuls Silvera, Victor Amadeo
A2 - Porto de Albuquerque, Joao
A2 - Moore, Kathleen Ann
A2 - Tapia, Andrea H.
PB - Information Systems for Crisis Response and Management, ISCRAM
T2 - 13th International Conference on Information Systems for Crisis Response and Management, ISCRAM 2016
Y2 - 22 May 2016 through 25 May 2016
ER -