2019
DOI: 10.24251/hicss.2019.271
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Collective Classification for Social Media Credibility Estimation

Abstract: We introduce a novel extension of the iterative classification algorithm to heterogeneous graphs and apply it to estimate credibility in social media. Given a heterogeneous graph of events, users, and websites derived from social media posts, and given prior knowledge of the credibility of a subset of graph nodes, the approach iteratively converges to a set of classifiers that estimate credibility of the remaining nodes. To measure the performance of this approach, we train on a set of manually labeled events … Show more

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Cited by 5 publications
(1 citation statement)
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“…Social media provide versatility of information in the form of pictures, videos, posts, tweets, live streams, stories; messages etc. for gratification of specific need of individuals and organizations (Campbell et al, 2019;Lee and Su, 2019;Nelson and Fleming, 2019;O'Brien et al, 2019;Stefanone et al, 2019;Virtanen, 2019).…”
Section: Introductionmentioning
confidence: 99%
“…Social media provide versatility of information in the form of pictures, videos, posts, tweets, live streams, stories; messages etc. for gratification of specific need of individuals and organizations (Campbell et al, 2019;Lee and Su, 2019;Nelson and Fleming, 2019;O'Brien et al, 2019;Stefanone et al, 2019;Virtanen, 2019).…”
Section: Introductionmentioning
confidence: 99%