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