Marrese-Taylor, E.Rodriguez Opazo, C.Balazs, J.Gould, S.Matsuo, Y.2023-04-062023-04-062020Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL 2020), 2020, pp.8-1897819521482480736-587Xhttps://hdl.handle.net/2440/137840From the Workshop: W19: The Second Grand-Challenge and Workshop on Human Multimodal Language (Challenge-HML)Despite 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.en© 2017 Association for Computational Linguistics. Materials published in or after 2016 are licensed on a Creative Commons Attribution 4.0 International License.Conference paper10.18653/v1/2020.challengehml-1.22023-04-05591332Rodriguez Opazo, C. [0000-0002-2108-3904]