DocumentCode
2392850
Title
Want to be Retweeted? Large Scale Analytics on Factors Impacting Retweet in Twitter Network
Author
Suh, Bongwon ; Hong, Lichan ; Pirolli, Peter ; Chi, Ed H.
Author_Institution
Palo Alto Res. Center, Inc., Palo Alto, CA, USA
fYear
2010
fDate
20-22 Aug. 2010
Firstpage
177
Lastpage
184
Abstract
Retweeting is the key mechanism for information diffusion in Twitter. It emerged as a simple yet powerful way of disseminating information in the Twitter social network. Even though a lot of information is shared in Twitter, little is known yet about how and why certain information spreads more widely than others. In this paper, we examine a number of features that might affect retweetability of tweets. We gathered content and contextual features from 74M tweets and used this data set to identify factors that are significantly associated with retweet rate. We also built a predictive retweet model. We found that, amongst content features, URLs and hashtags have strong relationships with retweetability. Amongst contextual features, the number of followers and followees as well as the age of the account seem to affect retweetability, while, interestingly, the number of past tweets does not predict retweetability of a user´s tweet. We believe that this research would inform the design of sensemaking and analytics tools for social media streams.
Keywords
media streaming; social networking (online); Twitter network; information diffusion; retweet model; social media streams; Correlation; Data analysis; Feature extraction; Mathematical model; Principal component analysis; Twitter;
fLanguage
English
Publisher
ieee
Conference_Titel
Social Computing (SocialCom), 2010 IEEE Second International Conference on
Conference_Location
Minneapolis, MN
Print_ISBN
978-1-4244-8439-3
Electronic_ISBN
978-0-7695-4211-9
Type
conf
DOI
10.1109/SocialCom.2010.33
Filename
5590452
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