Identifying persuasive qualities of decentralized peer-to-peer online social networks in public health

Sahiti Myneni, Sriram Iyengar, Nathan K. Cobb, Trevor Cohen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

Online social networks as behavior change support systems have been rapidly gaining in popularity. These networks have been studied by public health specialists from the point of view of traditional behavior change theories. However, scant research exists on the persuasive content of the messages exchanged between participants in such networks. In this paper, we use Persuasive Systems Design (PSD) model to develop a framework for identifying persuasive attributes in online social networks. This framework was applied to QuitNet, an online social network for smoking cessation. Results indicated that the communication in QuitNet had persuasive qualities such as reduction, simulation, social learning, reminders, suggestions, and rewards. Further, these features were predominantly found in messages related to "QuitNet-specific customs", "Quit progress", and "Family and friends". Use of this framework enables the development of quantitative relationships between persuasive attributes and behavior change outcomes experienced by network members.

Original languageEnglish (US)
Title of host publicationPersuasive Technology - 8th International Conference, PERSUASIVE 2013, Proceedings
Pages155-160
Number of pages6
DOIs
StatePublished - 2013
Externally publishedYes
Event8th International Conference on Persuasive Technology, PERSUASIVE 2013 - Sydney, NSW, Australia
Duration: Apr 3 2013Apr 5 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7822 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Conference on Persuasive Technology, PERSUASIVE 2013
Country/TerritoryAustralia
CitySydney, NSW
Period4/3/134/5/13

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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