2020 · 123 citations · 10 references
ComputingCommunicationComputer ScienceInformation RetrievalMachine LearningSocial Media AnalyticsMisinformation DetectionNews MediaOpinion MiningSocial MediaClassification AccuracyClassification Accuracy AnalysisClassification Accuracy AssessmentFake News AnalysisK-nearest NeighborsNearest Neighbor Matching
Consumption of news from social media is gradually increasing because of it's easy to access, cheap and more attractive and it's capable to spread the “fake news”. The widespread of fake news has latent adverse impressions on people and culture. Some people spread wrong information on social media to get the attention or financial and political gain. We need to be smarter at the recognition of fake or real news. The unique feature of detecting fake news on social media that make current detection algorithms ine □ ective or not appropriate. Thereafter is essential to consider secondary information. Secondary information may include social activities of user on social media. So, in this research work we are presenting a simple approach for detecting fake news on social media with the help of K-Nearest Neighbor classifier. We achieved a classification accuracy of this model approximate 79% tested against Facebook news posts dataset.
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Fake News Detection on Social Media
Kai Shu, Amy Sliva, Suhang Wang et al. · ACM SIGKDD Explorations Newsletter · 2017 · 3.1K citations
Novel Visual and Statistical Image Features for Microblogs News Verification
Zhiwei Jin, Juan Cao, Yongdong Zhang et al. · IEEE Transactions on Multimedia · 2016 · 462 citations
Detecting Fake News in Social Media Networks
Monther Aldwairi, Ali Alwahedi · Procedia Computer Science · 2018 · 358 citations · Full text