Retweetability analysis and prediction during Hurricane sandy

Venkata K. Neppalli, Murilo Cerqueira Medeiros, Cornelia Caragea, Doina Caragea, Andrea H. Tapia, Shane Halse

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

LanguageEnglish (US)
Title of host publicationISCRAM 2016 Conference Proceedings - 13th International Conference on Information Systems for Crisis Response and Management
PublisherInformation Systems for Crisis Response and Management, ISCRAM
ISBN (Electronic)9788460879848
StatePublished - Jan 1 2016
Event13th International Conference on Information Systems for Crisis Response and Management, ISCRAM 2016 - Rio de Janeiro, Brazil
Duration: May 22 2016May 25 2016

Other

Other13th International Conference on Information Systems for Crisis Response and Management, ISCRAM 2016
CountryBrazil
CityRio de Janeiro
Period5/22/165/25/16

Fingerprint

Hurricanes
Disasters
Experiments
Prediction
Twitter
Natural disasters

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Information Systems
  • Information Systems and Management
  • Electrical and Electronic Engineering

Cite this

Neppalli, V. K., Medeiros, M. C., Caragea, C., Caragea, D., Tapia, A. H., & Halse, S. (2016). Retweetability analysis and prediction during Hurricane sandy. In ISCRAM 2016 Conference Proceedings - 13th International Conference on Information Systems for Crisis Response and Management Information Systems for Crisis Response and Management, ISCRAM.
Neppalli, Venkata K. ; Medeiros, Murilo Cerqueira ; Caragea, Cornelia ; Caragea, Doina ; Tapia, Andrea H. ; Halse, Shane. / Retweetability analysis and prediction during Hurricane sandy. ISCRAM 2016 Conference Proceedings - 13th International Conference on Information Systems for Crisis Response and Management. Information Systems for Crisis Response and Management, ISCRAM, 2016.
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Neppalli, VK, Medeiros, MC, Caragea, C, Caragea, D, Tapia, AH & Halse, S 2016, Retweetability analysis and prediction during Hurricane sandy. in ISCRAM 2016 Conference Proceedings - 13th International Conference on Information Systems for Crisis Response and Management. Information Systems for Crisis Response and Management, ISCRAM, 13th International Conference on Information Systems for Crisis Response and Management, ISCRAM 2016, Rio de Janeiro, Brazil, 5/22/16.

Retweetability analysis and prediction during Hurricane sandy. / Neppalli, Venkata K.; Medeiros, Murilo Cerqueira; Caragea, Cornelia; Caragea, Doina; Tapia, Andrea H.; Halse, Shane.

ISCRAM 2016 Conference Proceedings - 13th International Conference on Information Systems for Crisis Response and Management. Information Systems for Crisis Response and Management, ISCRAM, 2016.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AU - Halse, Shane

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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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Neppalli VK, Medeiros MC, Caragea C, Caragea D, Tapia AH, Halse S. Retweetability analysis and prediction during Hurricane sandy. In ISCRAM 2016 Conference Proceedings - 13th International Conference on Information Systems for Crisis Response and Management. Information Systems for Crisis Response and Management, ISCRAM. 2016