{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T05:42:01Z","timestamp":1773207721038,"version":"3.50.1"},"reference-count":42,"publisher":"Emerald","issue":"2","license":[{"start":{"date-parts":[[2021,11,30]],"date-time":"2021-11-30T00:00:00Z","timestamp":1638230400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IMDS"],"published-print":{"date-parts":[[2022,2,1]]},"abstract":"Purpose<\/jats:title>Recommending suitable content for users of online health communities (OHCs) is critical for overcoming information overload problem and facilitate medical decision making, but remains not fully investigated. This study aims to provide a content recommendation approach to automatically match valuable health-related information for OHC members.<\/jats:p><\/jats:sec>Design\/methodology\/approach<\/jats:title>A framework of health-related content recommendation was proposed by leveraging rich social information in online communities. The authors constructed user influence relationship (UIR) utilizing users' interaction records, user profiles and user-generated content. The initial user rating matrix and the user post matching matrix were then created by analyzing text content of posts. Finally, the user rating matrix and the recommended content were generated for community members. Datasets were collected from an OHC to evaluate the effectiveness of the proposed approach.<\/jats:p><\/jats:sec>Findings<\/jats:title>The experimental results revealed that the proposed method statistically outperformed baseline models in content recommendation for users of OHCs.<\/jats:p><\/jats:sec>Research limitations\/implications<\/jats:title>The incorporation of social information can significantly enhance the performance of content recommendation in OHCs. The user post matching degree based on text analysis can improve the effectiveness of recommendation.<\/jats:p><\/jats:sec>Practical implications<\/jats:title>This study potentially contributes to the social support exchange and medical decision making of community members and the sustainable prosperity of OHCs.<\/jats:p><\/jats:sec>Originality\/value<\/jats:title>This study proposes a novel social content recommendation method for online health consumers based on UIRs by leveraging social information in OHCs. The results indicate the significance of social information in content recommendation of healthcare social media.<\/jats:p><\/jats:sec>","DOI":"10.1108\/imds-04-2021-0268","type":"journal-article","created":{"date-parts":[[2022,1,21]],"date-time":"2022-01-21T09:48:11Z","timestamp":1642758491000},"page":"345-364","source":"Crossref","is-referenced-by-count":15,"title":["Personalized content recommendation in online health communities"],"prefix":"10.1108","volume":"122","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9569-5938","authenticated-orcid":false,"given":"Hangzhou","family":"Yang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1762-4744","authenticated-orcid":false,"given":"Huiying","family":"Gao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","published-online":{"date-parts":[[2021,11,30]]},"reference":[{"key":"key2022020107361184400_ref001","first-page":"1","article-title":"Extracting food substitutes from food diary via distributional similarity","year":"2016"},{"key":"key2022020107361184400_ref002","first-page":"199","article-title":"Ensemble-based and hybrid recommender systems","year":"2016","journal-title":"Recommender Systems"},{"key":"key2022020107361184400_ref003","first-page":"1","article-title":"How multimorbid health information consumers interact in an online community Q&A platform","volume":"131","year":"2019","journal-title":"International Journal of Medical Informatics"},{"key":"key2022020107361184400_ref004","first-page":"993","article-title":"Latent Dirichlet allocation","volume":"3","year":"2003","journal-title":"Journal of Machine Learning Research"},{"key":"key2022020107361184400_ref005","doi-asserted-by":"crossref","first-page":"644","DOI":"10.1016\/j.knosys.2018.09.028","article-title":"User preferences modeling using Dirichlet process mixture model for a content-based recommender system","volume":"163","year":"2019","journal-title":"Knowledge Based Systems"},{"key":"key2022020107361184400_ref006","first-page":"785","article-title":"XGBoost: a scalable tree boosting system","year":"2016"},{"issue":"1","key":"key2022020107361184400_ref007","first-page":"71","article-title":"Social recommendations for Facebook brand pages","volume":"16","year":"2021","journal-title":"Journal of Theoretical and Applied Electronic Commerce Research"},{"issue":"5","key":"key2022020107361184400_ref008","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3407190","article-title":"Recommender systems leveraging multimedia content","volume":"53","year":"2020","journal-title":"ACM Computing Surveys"},{"issue":"1","key":"key2022020107361184400_ref009","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1007\/BF01386390","article-title":"A note on two problems in connection with graphs","volume":"1","year":"1959","journal-title":"Numerische Mathematik"},{"issue":"2","key":"key2022020107361184400_ref010","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1037\/0278-6133.23.2.207","article-title":"Social support and patient adherence to medical treatment: a meta-analysis","volume":"23","year":"2004","journal-title":"Health Psychology"},{"issue":"1","key":"key2022020107361184400_ref011","doi-asserted-by":"crossref","first-page":"63","DOI":"10.25300\/MISQ\/2018\/13211","article-title":"Top persuader prediction for social networks","volume":"42","year":"2018","journal-title":"MIS Quarterly"},{"key":"key2022020107361184400_ref012","first-page":"1","article-title":"User intimacy model for question recommendation in community question answering","volume":"188","year":"2020","journal-title":"Knowledge-Based Systems"},{"issue":"1","key":"key2022020107361184400_ref013","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1016\/j.ejor.2017.07.005","article-title":"A framework for configuring collaborative filtering-based recommendations derived from purchase data","volume":"265","year":"2018","journal-title":"European Journal of Operational Research"},{"issue":"1","key":"key2022020107361184400_ref014","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1006\/jeth.1996.0108","article-title":"A strategic model of social and economic networks","volume":"71","year":"1996","journal-title":"Journal of Economic Theory"},{"key":"key2022020107361184400_ref015","first-page":"538","article-title":"SimRank: a measure of structural-context similarity","year":"2002"},{"key":"key2022020107361184400_ref016","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/j.artmed.2017.03.002","article-title":"User recommendation in healthcare social media by assessing user similarity in heterogeneous network","volume":"81","year":"2017","journal-title":"Artificial Intelligence in Medicine"},{"issue":"1","key":"key2022020107361184400_ref017","first-page":"1","article-title":"A hybrid recommendation model in social media based on deep emotion analysis and multi-source view fusion","volume":"9","year":"2020","journal-title":"Journal of Cloud Computing-Advances Systems and Applications"},{"issue":"4","key":"key2022020107361184400_ref018","doi-asserted-by":"crossref","first-page":"1041","DOI":"10.2307\/2579133","article-title":"Networks of political action: toward theory construction","volume":"68","year":"1990","journal-title":"Social Forces"},{"issue":"4","key":"key2022020107361184400_ref019","doi-asserted-by":"crossref","first-page":"683","DOI":"10.1108\/IMDS-02-2017-0044","article-title":"Recommending valuable ideas in an open innovation community: a text mining approach to information overload problem","volume":"118","year":"2018","journal-title":"Industrial Management and Data Systems"},{"issue":"3","key":"key2022020107361184400_ref020","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3319528","article-title":"Integrating multi-level tag recommendation with external knowledge bases for automatic question answering","volume":"19","year":"2019","journal-title":"ACM Transactions on Internet Technology"},{"issue":"8","key":"key2022020107361184400_ref021","doi-asserted-by":"crossref","first-page":"1802","DOI":"10.1108\/IMDS-04-2019-0251","article-title":"Online news recommendations based on topic modeling and online interest adjustment","volume":"119","year":"2019","journal-title":"Industrial Management and Data Systems"},{"issue":"6","key":"key2022020107361184400_ref022","doi-asserted-by":"crossref","first-page":"821","DOI":"10.1108\/AJIM-02-2019-0048","article-title":"Long story short: finding health advice with informative summaries on health social media","volume":"71","year":"2019","journal-title":"Aslib Journal of Information Management"},{"issue":"2","key":"key2022020107361184400_ref023","first-page":"388","article-title":"Co-attention memory network for multimodal Microblog's hashtag recommendation","volume":"33","year":"2021","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"key2022020107361184400_ref024","first-page":"1","article-title":"An intelligent fuzzy rule-based personalized news recommendation using social media mining","volume":"2020","year":"2020","journal-title":"Computational Intelligence and Neuroscience"},{"key":"key2022020107361184400_ref025","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1146\/annurev.soc.27.1.415","article-title":"Birds of a feather: homophily in social networks","volume":"27","year":"2001","journal-title":"Annual Review of Sociology"},{"key":"key2022020107361184400_ref026","first-page":"1","article-title":"Concept based auto-assignment of healthcare questions to domain experts in online Q&A communities","volume":"137","year":"2020","journal-title":"International Journal of Medical Informatics"},{"key":"key2022020107361184400_ref027","first-page":"1","article-title":"Mutual information-based recommender system using autoencoder","volume":"109","year":"2021","journal-title":"Applied Soft Computing"},{"key":"key2022020107361184400_ref028","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1016\/j.elerap.2018.01.007","article-title":"Do reviews from friends and the crowd affect online consumer posting behaviour differently?","volume":"29","year":"2018","journal-title":"Electronic Commerce Research and Applications"},{"issue":"2","key":"key2022020107361184400_ref029","first-page":"1","article-title":"On the negative impact of social influence in recommender systems: a study of bribery in collaborative hybrid algorithms","volume":"57","year":"2020","journal-title":"Information Processing and Management"},{"key":"key2022020107361184400_ref030","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ijmedinf.2017.02.003","article-title":"Online social support for obese adults: exploring the role of forum activity","volume":"101","year":"2017","journal-title":"International Journal of Medical Informatics"},{"issue":"1","key":"key2022020107361184400_ref031","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1016\/0378-8733(90)90021-Z","article-title":"Individual and network influences on the adoption and perceived outcomes of electronic messaging","volume":"12","year":"1990","journal-title":"Social Networks"},{"issue":"5762","key":"key2022020107361184400_ref032","doi-asserted-by":"crossref","first-page":"854","DOI":"10.1126\/science.1121066","article-title":"Experimental study of inequality and unpredictability in an artificial cultural market","volume":"311","year":"2006","journal-title":"Science"},{"key":"key2022020107361184400_ref033","first-page":"2","article-title":"Utilizing collaborative filtering to recommend opportunities for positive affect in daily life","year":"2019"},{"issue":"5","key":"key2022020107361184400_ref034","doi-asserted-by":"crossref","first-page":"827","DOI":"10.1109\/TKDE.2019.2895033","article-title":"A hybrid e-learning recommendation approach based on learners' influence propagation","volume":"32","year":"2020","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"key2022020107361184400_ref035","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.dss.2018.10.005","article-title":"Mining user-generated content in an online smoking cessation community to identify smoking status: a machine learning approach","volume":"116","year":"2019","journal-title":"Decision Support Systems"},{"issue":"2","key":"key2022020107361184400_ref036","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1006\/game.2000.0803","article-title":"A dynamic model of network formation","volume":"34","year":"2001","journal-title":"Games and Economic Behavior"},{"issue":"4","key":"key2022020107361184400_ref037","doi-asserted-by":"crossref","first-page":"690","DOI":"10.1287\/isre.2014.0538","article-title":"Feeling blue? Go online: an empirical study of social support among patients","volume":"25","year":"2014","journal-title":"Information Systems Research"},{"issue":"3","key":"key2022020107361184400_ref038","doi-asserted-by":"crossref","first-page":"496","DOI":"10.1287\/isre.2015.0585","article-title":"Network dynamics: how can we find patients like us?","volume":"26","year":"2015","journal-title":"Information Systems Research"},{"issue":"9","key":"key2022020107361184400_ref039","first-page":"1","article-title":"Toward sustainable virtualized healthcare: extracting medical entities from Chinese online health consultations using deep neural networks","volume":"10","year":"2018","journal-title":"Sustainability"},{"issue":"5","key":"key2022020107361184400_ref040","first-page":"1","article-title":"A survey of collaborative filtering based social recommender systems","volume":"41","year":"2014","journal-title":"Computer Communications"},{"issue":"5","key":"key2022020107361184400_ref041","doi-asserted-by":"crossref","first-page":"635","DOI":"10.1177\/0165551516657712","article-title":"A social recommender system by combining social network and sentiment similarity: a case study of healthcare","volume":"43","year":"2017","journal-title":"Journal of Information Science"},{"key":"key2022020107361184400_ref042","first-page":"3273","article-title":"A survey of collaborative filtering-based recommender systems for mobile Internet applications","volume":"4","year":"2017","journal-title":"IEEE Access"}],"container-title":["Industrial Management & Data Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/IMDS-04-2021-0268\/full\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/IMDS-04-2021-0268\/full\/html","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T21:51:58Z","timestamp":1753393918000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.emerald.com\/imds\/article\/122\/2\/345-364\/183699"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,30]]},"references-count":42,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2021,11,30]]},"published-print":{"date-parts":[[2022,2,1]]}},"alternative-id":["10.1108\/IMDS-04-2021-0268"],"URL":"https:\/\/doi.org\/10.1108\/imds-04-2021-0268","relation":{},"ISSN":["0263-5577"],"issn-type":[{"value":"0263-5577","type":"print"}],"subject":[],"published":{"date-parts":[[2021,11,30]]}}}