A Multi-modal Approach to Fine-grained Opinion Mining on Video Reviews

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dc.contributor.authorMarrese-Taylor, E.
dc.contributor.authorRodriguez Opazo, C.
dc.contributor.authorBalazs, J.
dc.contributor.authorGould, S.
dc.contributor.authorMatsuo, Y.
dc.contributor.conference58th Annual Meeting of the Association for Computational Linguistics (ACL) (5 Jul 2020 - 10 Jul 2020 : Seattle, USA)
dc.date.issued2020
dc.descriptionFrom the Workshop: W19: The Second Grand-Challenge and Workshop on Human Multimodal Language (Challenge-HML)
dc.description.abstractDespite the recent advances in opinion mining for written reviews, few works have tackled the problem on other sources of reviews. In light of this issue, we propose a multimodal approach for mining fine-grained opinions from video reviews that is able to determine the aspects of the item under review that are being discussed and the sentiment orientation towards them. Our approach works at the sentence level without the need for time annotations and uses features derived from the audio, video and language transcriptions of its contents. We evaluate our approach on two datasets and show that leveraging the video and audio modalities consistently provides increased performance over text-only baselines, providing evidence these extra modalities are key in better understanding video reviews.
dc.description.statementofresponsibilityEdison Marrese-Taylor, Cristian Rodriguez-Opazo, Jorge A. Balazs, Stephen Gould and Yutaka Matsuo
dc.identifier.citationProceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL 2020), 2020, pp.8-18
dc.identifier.doi10.18653/v1/2020.challengehml-1.2
dc.identifier.isbn9781952148248
dc.identifier.issn0736-587X
dc.identifier.orcidRodriguez Opazo, C. [0000-0002-2108-3904]
dc.identifier.urihttps://hdl.handle.net/2440/137840
dc.language.isoen
dc.publisherAssociation for Computational Linguistics
dc.rights© 2017 Association for Computational Linguistics. Materials published in or after 2016 are licensed on a Creative Commons Attribution 4.0 International License.
dc.source.urihttps://virtual.acl2020.org/workshop_W19.html
dc.titleA Multi-modal Approach to Fine-grained Opinion Mining on Video Reviews
dc.typeConference paper
pubs.publication-statusPublished

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