Publication | Closed Access
The CERTH-UNITN Participation @ Verifying Multimedia Use 2015
19
Citations
2
References
2015
Year
Abuse DetectionEngineeringVerificationInformation ForensicsMultimedia AnalysisCommunicationText MiningSocial MediaData ScienceMultimedia ContentDisinformation DetectionContent AnalysisMobile MultimediaSocial Medium MiningAgreement-retraining MethodTrustComputer ScienceMultimedia ManagementAvailable FeaturesSocial ComputingArts
We propose an approach that predicts whether a tweet, which is accompanied by multimedia content (image/video), is trustworthy or deceptive. We test dierent combinations of quality and trust-oriented features (tweet-based, userbased and forensics) in tandem with a standard classication and an agreement-retraining technique, with the goal of predicting the most likely label (fake or real) for each tweet. The experiments carried out on the Verifying Multimedia Use dataset show that the best performance is achieved when using all available features in combination with the agreement-retraining method.
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