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=== Visual features ===
One of the main advantages of analyzing videos with respect to texts alone, is the presence of rich sentiment cues in visual data.<ref>{{cite journal |last1=Poria |first1=Soujanya |last2=Cambria |first2=Erik |last3=Hazarika |first3=Devamanyu |last4=Majumder |first4=Navonil |last5=Zadeh |first5=Amir |last6=Morency |first6=Louis-Philippe |title=Context-Dependent Sentiment Analysis in User-Generated Videos |journal=Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) |pages=873–883 |date=2017 |doi=10.18653/v1/p17-1081 |doi-access=free }}</ref> Visual features include [[facial expression]]s, which are of paramount importance in capturing sentiments and [[emotion]]s, as they are a main channel of forming a person's present state of mind.<ref name="s1" /> Specifically, [[smile]], is considered to be one of the most predictive visual cues in multimodal sentiment analysis.<ref name="s2" /> OpenFace is an open-source facial analysis toolkit available for extracting and understanding such visual features.<ref>{{cite
== Fusion techniques ==
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