Friend recommendation for healthy weight in social networks A novel approach to weight loss

Anming Li, Wai Ting Ngai, Junyi Chai

Research output: Journal article publicationJournal articleAcademic researchpeer-review

4 Citations (Scopus)

Abstract

Purpose-The purpose of this paper is to propose a new approach recommending friends to social networking users who are also using weight loss app in the context of social networks. Design/methodology/approach-Social network has been recognized as an effective way to enhance overweight and obesity interventions in past studies. However, effective measures integrating social network with weight loss are very limited in the healthcare area. To bridge this gap, this study develops a measure for friend recommendation using the data obtained by weight loss apps; designs methods to model weight-gain-related behaviors (WGRB); constructs a novel "behavior network;" and develops two measurements in experiments to examine the proposed approach. Findings-The approach for friend recommendation is based on Friend Recommendation for Health Weight (FRHW) algorithm. By running this algorithm on a real data set, the experiment results show that the algorithm can recommend a friend who has a healthy lifestyle to a target user. The advantages of the proposed mechanism have been well justified via comparisons with popular friend recommenders in past studies. Originality/value-The conventional methods for friend recommenders in social networks are only concerned with similarities of pairs rather than interactions between people. The system cannot account for the potential influences among people. The method pioneers to model a WGRB as recommendation mechanismthat allow recommended friends to simultaneously fulfill two criteria. They are: first, similarity to the target person; and second, ensuring the positive influence toward weight loss. The second criterion is obviously important in practice and thus the approach is valuable to the literature.
Original languageEnglish
Pages (from-to)1251-1268
Number of pages18
JournalIndustrial Management and Data Systems
Volume115
Issue number7
DOIs
Publication statusPublished - 1 Jan 2015

Keywords

  • Healthcare
  • Obesity
  • Recommendation
  • Social network

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Industrial relations
  • Strategy and Management
  • Management Information Systems
  • Computer Science Applications

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