June 6, 2017 Conference paper Open Access

Olga Papadopoulou; Markos Zampoglou; Symeon Papadopoulos; Yiannis Kompatsiaris

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    <subfield code="a">Video verification</subfield>
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    <subfield code="a">Context analysis</subfield>
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    <subfield code="a">Symeon Papadopoulos</subfield>
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    <subfield code="a">Yiannis Kompatsiaris</subfield>
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    <subfield code="u">CERTH-ITI, Thessaloniki, Greece</subfield>
    <subfield code="a">Olga Papadopoulou</subfield>
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    <subfield code="a">Web Video Verification using Contextual Cues</subfield>
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    <subfield code="a">In Video Veritas – Verification of Social Media Video Content for the News Industry</subfield>
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    <subfield code="a">&lt;p&gt;As news agencies and the public increasingly rely on User-Generated Content, content verification is vital for news producers and consumers alike. We present a novel approach for verifying Web videos by analyzing their online context. It is based on supervised learning on contextual features: one feature set is based on an existing approach for tweet verification adapted to video comments. The other is based on video metadata, such as the video description, likes/dislikes, and uploader information.&lt;br&gt;
We evaluate both on a dataset of real and fake videos from YouTube, and demonstrate their effectiveness (F-scores: 0.82, 0.79). We then explore their complementarity and show that under an optimal fusion scheme, the classifier would reach an F-score of 0.9. We finally study the performance of the classifier through time, as more comments accumulate, emulating a real-time verification setting.&lt;/p&gt;</subfield>
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