A model-free scheme for meme ranking in social media

Saike He, Xiaolong Zheng, Dajun Zeng

Research output: Contribution to journalArticle

10 Scopus citations

Abstract

The prevalence of social media has greatly catalyzed the dissemination and proliferation of online memes (e.g., ideas, topics, melodies, and tags). However, this information abundance is exceeding the capability of online users to consume it. Ranking memes based on their popularities could promote online advertisement and content distribution. Despite such importance, few existing work can solve this problem well. They are either daunted by unpractical assumptions or incapability of characterizing dynamic information. As such, in this paper, we elaborate a model-free scheme to rank online memes in the context of social media. This scheme is capable to characterize the nonlinear interactions of online users, which mark the process of meme diffusion. Empirical studies on two large-scale, real-world datasets (one in English and one in Chinese) demonstrate the effectiveness and robustness of the proposed scheme. In addition, due to its fine-grained modeling of user dynamics, this ranking scheme can also be utilized to explain meme popularity through the lens of social influence.

Original languageEnglish (US)
Pages (from-to)1-11
Number of pages11
JournalDecision Support Systems
Volume81
DOIs
StatePublished - Jan 1 2016

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Keywords

  • Meme ranking
  • Model-free scheme
  • Transfer entropy

ASJC Scopus subject areas

  • Management Information Systems
  • Information Systems
  • Information Systems and Management
  • Arts and Humanities (miscellaneous)
  • Developmental and Educational Psychology

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