Average is boring: how similarity kills a meme's success.

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 Rep

journal_title

Scientific reports

authors

Coscia M

doi

10.1038/srep06477

subject

Has Abstract

pub_date

2014-09-26 00:00:00

pages

6477

issn

2045-2322

pii

srep06477

journal_volume

4

pub_type

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