Abstract:
:Every day we are exposed to different ideas, or memes, competing with each other for our attention. Previous research explained popularity and persistence heterogeneity of memes by assuming them in competition for limited attention resources, distributed in a heterogeneous social network. Little has been said about what characteristics make a specific meme more likely to be successful. We propose a similarity-based explanation: memes with higher similarity to other memes have a significant disadvantage in their potential popularity. We employ a meme similarity measure based on semantic text analysis and computer vision to prove that a meme is more likely to be successful and to thrive if its characteristics make it unique. Our results show that indeed successful memes are located in the periphery of the meme similarity space and that our similarity measure is a promising predictor of a meme success.
journal_name
Sci Repjournal_title
Scientific reportsauthors
Coscia Mdoi
10.1038/srep06477subject
Has Abstractpub_date
2014-09-26 00:00:00pages
6477issn
2045-2322pii
srep06477journal_volume
4pub_type
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