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        <title>Cross-Lingual Cross-Platform Rumor Verification Pivoting on Multimedia Content</title>
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        <namePart type="given">Weiming</namePart>
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        <namePart type="family">Su</namePart>
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    <name type="personal">
        <namePart type="given">Zhou</namePart>
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        <dateIssued>2018-oct-nov</dateIssued>
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            <title>Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing</title>
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            <namePart type="given">Ellen</namePart>
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            <namePart type="given">David</namePart>
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            <namePart type="given">Jun’ichi</namePart>
            <namePart type="family">Tsujii</namePart>
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    <abstract>With the increasing popularity of smart devices, rumors with multimedia content become more and more common on social networks. The multimedia information usually makes rumors look more convincing. Therefore, finding an automatic approach to verify rumors with multimedia content is a pressing task. Previous rumor verification research only utilizes multimedia as input features. We propose not to use the multimedia content but to find external information in other news platforms pivoting on it. We introduce a new features set, cross-lingual cross-platform features that leverage the semantic similarity between the rumors and the external information. When implemented, machine learning methods utilizing such features achieved the state-of-the-art rumor verification results.</abstract>
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    <identifier type="doi">10.18653/v1/D18-1385</identifier>
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        <date>2018-oct-nov</date>
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%0 Conference Proceedings
%T Cross-Lingual Cross-Platform Rumor Verification Pivoting on Multimedia Content
%A Wen, Weiming
%A Su, Songwen
%A Yu, Zhou
%Y Riloff, Ellen
%Y Chiang, David
%Y Hockenmaier, Julia
%Y Tsujii, Jun’ichi
%S Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
%D 2018
%8 oct nov
%I Association for Computational Linguistics
%C Brussels, Belgium
%F wen-etal-2018-cross
%X With the increasing popularity of smart devices, rumors with multimedia content become more and more common on social networks. The multimedia information usually makes rumors look more convincing. Therefore, finding an automatic approach to verify rumors with multimedia content is a pressing task. Previous rumor verification research only utilizes multimedia as input features. We propose not to use the multimedia content but to find external information in other news platforms pivoting on it. We introduce a new features set, cross-lingual cross-platform features that leverage the semantic similarity between the rumors and the external information. When implemented, machine learning methods utilizing such features achieved the state-of-the-art rumor verification results.
%R 10.18653/v1/D18-1385
%U https://aclanthology.org/D18-1385
%U https://doi.org/10.18653/v1/D18-1385
%P 3487-3496

Markdown (Informal)

[Cross-Lingual Cross-Platform Rumor Verification Pivoting on Multimedia Content](https://aclanthology.org/D18-1385) (Wen et al., EMNLP 2018)

• Cross-Lingual Cross-Platform Rumor Verification Pivoting on Multimedia Content (Wen et al., EMNLP 2018)

ACL

• Weiming Wen, Songwen Su, and Zhou Yu. 2018. Cross-Lingual Cross-Platform Rumor Verification Pivoting on Multimedia Content. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 3487–3496, Brussels, Belgium. Association for Computational Linguistics.