Analyzing behavior of the influential across social media

Nitin Agarwal, Shamanth Kumar, Huiji Gao, Reza Zafarani, Huan Liu

Research output: Chapter in Book/Report/Conference proceedingChapter

9 Scopus citations

Abstract

The popularity of social media as an information source, in the recent years has spawned several interesting applications, and consequently challenges to using it effectively. Identifying and targeting influential individuals on sites is a crucial way to maximize the returns of advertising and marketing efforts. Recently, this problem has been well studied in the context of blogs, microblogs, and other forms of social media sites. Understanding how these users behave on a social media site and even across social media sites will lead to more effective strategies. In this book chapter, we present existing techniques to identify influential individuals in a social media site. We present a user identification strategy, which can help us to identify influential individuals across sites. Using a combination of these ap-proaches we present a study of the characteristics and behavior of influential indi-viduals across sites. We evaluate our approaches on several of the popular social media sites. Among other interesting findings, we discover that influential individ-uals on one site are more likely to be influential on other sites as well. We also find that influential users are more likely to connect to other influential individuals.

Original languageEnglish (US)
Title of host publicationBehavior Computing: Modeling, Analysis, Mining and Decision
PublisherSpringer-Verlag London Ltd
Pages3-19
Number of pages17
ISBN (Print)9781447129691, 9781447129684
DOIs
StatePublished - Jan 1 2012

ASJC Scopus subject areas

  • General Computer Science

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