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A graph-based comprehensive reputation model: exploiting the social context of opinions to enhance trust in social commerce
Högskolan Dalarna, Akademin Industri och samhälle, Informatik.ORCID-id: 0000-0003-3681-8173
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2015 (Engelska)Ingår i: Information Sciences, ISSN 0020-0255, E-ISSN 1872-6291, Vol. 318, s. 51-72Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

Social commerce is a promising new paradigm of e-commerce. Given the open and dynamic nature of social media infrastructure, the governance structures of social commerce are usually realized through reputation mechanisms. However, the existing approaches to the prediction of trust in future interactions are based on personal observations and/or publicly shared information in social commerce application. As a result, the indications are unreliable and biased because of limited first-hand information and stake-holder manipulation for personal strategic interests. Methods that extract trust values from social links among users can improve the performance of reputation mechanisms. Nonetheless, these links may not always be available and are typically sparse in social commerce, especially for new users. Thus, this study proposes a new graph-based comprehensive reputation model to build trust by fully exploiting the social context of opinions based on the activities and relationship networks of opinion contributors. The proposed model incorporates the behavioral activities and social relationship reputations of users to combat the scarcity of first-hand information and identifies a set of critical trust factors to mitigate the subjectivity of opinions and the dynamics of behaviors. Furthermore, we enhance the model by developing a novel deception filtering approach to discard "bad-mouthing" opinions and by exploiting a personalized direct distrust (risk) metric to identify malicious providers. Experimental results show that the proposed reputation model can outperform other trust and reputation models in most cases. (C) 2014 Elsevier Inc. All rights reserved.

Ort, förlag, år, upplaga, sidor
2015. Vol. 318, s. 51-72
Nyckelord [en]
Social commerce, Reputation, Social context, Risk tolerance
Nationell ämneskategori
Systemvetenskap, informationssystem och informatik
Forskningsämne
Komplexa system - mikrodataanalys
Identifikatorer
URN: urn:nbn:se:du-18932DOI: 10.1016/j.ins.2014.09.036ISI: 000357707600005OAI: oai:DiVA.org:du-18932DiVA, id: diva2:843732
Tillgänglig från: 2015-07-31 Skapad: 2015-07-31 Senast uppdaterad: 2018-01-11Bibliografiskt granskad

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Song, William Wei

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Totalt: 565 träffar
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