Friend recommendation for healthy weight in social networks: A novel approach to weight loss. Issue 7 (10th August 2015)
- Record Type:
- Journal Article
- Title:
- Friend recommendation for healthy weight in social networks: A novel approach to weight loss. Issue 7 (10th August 2015)
- Main Title:
- Friend recommendation for healthy weight in social networks
- Authors:
- Li, Anming
Ngai, Eric W.T.
Chai, Junyi - Abstract:
- 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 mechanism that allowAbstract : 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 mechanism that 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. … (more)
- Is Part Of:
- Industrial management & data systems. Volume 115:Issue 7(2015)
- Journal:
- Industrial management & data systems
- Issue:
- Volume 115:Issue 7(2015)
- Issue Display:
- Volume 115, Issue 7 (2015)
- Year:
- 2015
- Volume:
- 115
- Issue:
- 7
- Issue Sort Value:
- 2015-0115-0007-0000
- Page Start:
- 1251
- Page End:
- 1268
- Publication Date:
- 2015-08-10
- Subjects:
- Healthcare -- Obesity -- Social network -- Recommendation
Industrial management -- Periodicals
Electronic data processing -- Periodicals
Business -- Periodicals
Industrial management -- Great Britain -- Periodicals
658.05 - Journal URLs:
- http://www.emeraldinsight.com/0263-5577.htm ↗
http://www.emeraldinsight.com/ ↗ - DOI:
- 10.1108/IMDS-04-2015-0130 ↗
- Languages:
- English
- ISSNs:
- 0263-5577
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4457.715000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 8149.xml