Social networks enable multimedia sharing between worldwide users, however, there is no automatic mechanism implemented aiming to verifying multimedia use. This has been known as a highly challenging problem due to the variety of media types and huge amount of information they convey. As a participating team of MediaEval 2016, we propose a hybrid approach for detecting misused multimedia on Twitter which has been known as Verifying Multimedia Use task. Specifically, we designed a verfication system that can answer how likely an associated multimedia file is fake based on multiple forensic features and textual features, which were acquired by performing online text search and image reverse search. Next, effective post-based features and user-based features are utilized to validate the credibility of tweet posts. Finally, based on the assumption that a tweet sharing fake images or videos is likely to be fake, credibility scores of tweet posts and associated multimedia are fused to detect misused multimedia.
A Hybrid Approach for Multimedia Use Verification / Phan, Quoc Tin; Alessandro, Budroni; Pasquini, Cecilia; De Natale, Francesco. - ELETTRONICO. - (2016), pp. [1]-[3]. (Intervento presentato al convegno MediaEval tenutosi a The Netherlands nel October 20-21, 2016).
A Hybrid Approach for Multimedia Use Verification
Phan, Quoc Tin;Pasquini, Cecilia;De Natale, Francesco
2016-01-01
Abstract
Social networks enable multimedia sharing between worldwide users, however, there is no automatic mechanism implemented aiming to verifying multimedia use. This has been known as a highly challenging problem due to the variety of media types and huge amount of information they convey. As a participating team of MediaEval 2016, we propose a hybrid approach for detecting misused multimedia on Twitter which has been known as Verifying Multimedia Use task. Specifically, we designed a verfication system that can answer how likely an associated multimedia file is fake based on multiple forensic features and textual features, which were acquired by performing online text search and image reverse search. Next, effective post-based features and user-based features are utilized to validate the credibility of tweet posts. Finally, based on the assumption that a tweet sharing fake images or videos is likely to be fake, credibility scores of tweet posts and associated multimedia are fused to detect misused multimedia.File | Dimensione | Formato | |
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