How to find opinion leader on the online social network?

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dc.contributor.authorJin, Bailu
dc.contributor.authorZou, Mengbang
dc.contributor.authorWei, Zhuangkun
dc.contributor.authorGuo, Weisi
dc.date.accessioned2025-04-15T13:18:16Z
dc.date.available2025-04-15T13:18:16Z
dc.date.freetoread2025-04-15
dc.date.issued2025-05-01
dc.date.pubOnline2025-04-04
dc.description.abstractOnline social networks (OSNs) provide a platform for individuals to share information, exchange ideas, and build social connections beyond in-person interactions. For a specific topic or community, opinion leaders are individuals who have a significant influence on others’ opinions. Detecting opinion leaders and modeling influence dynamics is crucial as they play a vital role in shaping public opinion and driving conversations. Existing research have extensively explored various graph-based and psychology-based methods for detecting opinion leaders, but there is a lack of cross-disciplinary consensus between definitions and methods. For example, node centrality in graph theory does not necessarily align with the opinion leader concepts in social psychology. This review paper aims to address this multi-disciplinary research area by introducing and connecting the diverse methodologies for identifying influential nodes. The key novelty is to review connections and cross-compare different multi-disciplinary approaches that have origins in: social theory, graph theory, compressed sensing theory, and control theory. Our first contribution is to develop cross-disciplinary discussion on how they tell a different tale of networked influence. Our second contribution is to propose trans-disciplinary research method on embedding socio-physical influence models into graph signal analysis. We showcase inter- and trans-disciplinary methods through a Twitter case study to compare their performance and elucidate the research progression with relation to psychology theory. We hope the comparative analysis can inspire further research in this cross-disciplinary area.
dc.description.journalNameApplied Intelligence
dc.description.sponsorshipUSAF OFSR|FA8655-20-1-7031
dc.description.sponsorshipThe work is supported by "Networked Social Influence and Acceptance in a New Age of Crises", funded by USAF OFSR under Grant No.: FA8655-20-1-7031, and is partly supported by the Engineering and Physical Sciences Research Council grant number: EP/V026763/1.
dc.identifier.citationJin B, Zou M, Wei Z, Guo W. (2025) How to find opinion leader on the online social network?. Applied Intelligence, Volume 55, Issue 7, Article number 624
dc.identifier.eissn1573-7497
dc.identifier.elementsID672716
dc.identifier.issn0924-669X
dc.identifier.issueNo7
dc.identifier.paperNo624
dc.identifier.urihttps://doi.org/10.1007/s10489-025-06525-y
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/23766
dc.identifier.volumeNo55
dc.languageEnglish
dc.language.isoen
dc.publisherSpringer
dc.publisher.urihttps://link.springer.com/article/10.1007/s10489-025-06525-y
dc.relation.isreferencedbyhttps://github.com/AlminaJin/OpinionLeaderDetection.git
dc.relation.isreferencedbyhttps://github.com/AlminaJin/OpinionLeaderDetection.git
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subject4605 Data Management and Data Science
dc.subject46 Information and Computing Sciences
dc.subjectArtificial Intelligence & Image Processing
dc.subject46 Information and computing sciences
dc.titleHow to find opinion leader on the online social network?
dc.typeArticle
dcterms.dateAccepted2025-03-28

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