DocumentCode :
43459
Title :
Forecasti ng Virality [Dataflow]
Author :
Anderson, Matthew
Volume :
51
Issue :
4
fYear :
2014
fDate :
Apr-14
Firstpage :
76
Lastpage :
76
Abstract :
Memes, like Rickrolling or LOLcats, are the invasive species of social network ecosystems such as Facebook and Twitter. "Viral hashtags are so interesting that even at first sight, you just start to use them," says Yong-Yeol Ahn, assistant professor at Indiana University\´s School of Informatics and Computing. Ahn and his coauthors have isolated the network properties of memes and turned them into a forecasting tool, enabling the prediction of which Twitter hashtags will go viral nearly two out of three times based on how the hashtag is shared in its early stages. Ahn says later this spring they\´ll be publishing follow-up research that looks at predicting just how big a splash a viral meme will make.
fLanguage :
English
Journal_Title :
Spectrum, IEEE
Publisher :
ieee
ISSN :
0018-9235
Type :
jour
DOI :
10.1109/MSPEC.2014.6776315
Filename :
6776315
Link To Document :
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