Community aware recommendation system for social commerce

dc.contributor.guideJayashree P
dc.coverage.spatialCommunity aware recommendation system for social commerce
dc.creator.researcherLaila K
dc.date.accessioned2025-01-20T05:10:48Z
dc.date.available2025-01-20T05:10:48Z
dc.date.awarded2025
dc.date.completed2024
dc.date.registered
dc.description.abstractnewline Social commerce, also known as social shopping, is a form of e-commerce that leverages social media platforms as a means to market and sell products directly to end users. Over 80% of the online population in Asian countries like India, Thailand, and China are social buyers [102]. They often turn to social media for ideas and recommendations before making a purchase. According to 2022 survey, approximately one-third of the social buyers prefer Facebook, Twitter, and Instagram as their favorite social commerce platforms for online purchase. It is necessary to integrate social media into e-commerce to effectively analyze recommendation systems. One of the key features and strategies of social commerce is User Generated Content (UGC) which includes images, videos and customer reviews. This research work is based on the online reviews collected from social networks and e-commerce platforms. Essentially, not all the information sifts through from these online platforms is accurate and trustworthy. The objective of this research is to develop a community-aware product recommendation engine based on product ranking and analysis of the trustworthiness of the tweeters on Twitter, as well as spam detection in e-commerce reviews with explainability.
dc.description.note
dc.format.accompanyingmaterialNone
dc.format.dimensionsxx,123.
dc.format.extent21cm
dc.identifier.researcherid
dc.identifier.urihttp://hdl.handle.net/10603/616220
dc.languageEnglish
dc.publisher.institutionFaculty of Information and Communication Engineering
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.relationp.113-122.
dc.rightsuniversity
dc.source.universityUniversity
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Information Systems
dc.subject.keywordEngineering and Technology
dc.titleCommunity aware recommendation system for social commerce
dc.title.alternative
dc.type.degreePh.D.

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