Meme ranking to maximize posts virality in microblogging platforms

Francesco Bonchi, Carlos Castillo, Dino Ienco

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

Microblogging is a modern communication paradigm in which users post bits of information, or "memes" as we call them, that are brief text updates or micromedia such as photos, video or audio clips. Once a user post a meme, it become visible to the user community. When a user finds a meme of another user interesting, she can eventually repost it, thus allowing memes to propagate virally trough the social network. In this paper we introduce the meme ranking problem, as the problem of selecting which k memes (among the ones posted by their contacts) to show to users when they log into the system. The objective is to maximize the overall activity of the network, that is, the total number of reposts that occur. We deeply characterize the problem showing that not only exact solutions are unfeasible, but also approximated solutions are prohibitive to be adopted in an on-line setting. Therefore we devise a set of heuristics and we compare them trough an extensive simulation based on the real-world Yahoo! Meme social graph, using parameters learnt from real logs of meme propagations. Our experimentation demonstrates the effectiveness and feasibility of these methods.

Original languageEnglish
Pages (from-to)211-239
Number of pages29
JournalJournal of Intelligent Information Systems
Volume40
Issue number2
DOIs
Publication statusPublished - 1 Apr 2013

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Keywords

  • Feed ranking
  • Information propagation
  • Social network analysis

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Hardware and Architecture
  • Computer Networks and Communications
  • Artificial Intelligence

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