Journal of Computer Science

Multimodal Sentiment Analysis: A Comparison Study

Yahia Hasan Jazyah and Intisar O. Hussien

Journal of Computer Science


Sentiments and emotions play a pivotal role in our daily lives. They assist decision making, learning, communication and situation awareness in human environments. Sentiment analysis is mainly focused on the automatic recognition of opinions’ polarity, as positive or negative. Nowadays, sentiment analysis is replacing the old web based survey and traditional survey methods that conducted by deferent companies for finding public opinion about entities like products and services in order to improve their marketing strategy and product of advertisement, at the same time sentiment analysis improves customer service. Large number of videos is being uploaded online every day. Video files contain text, visual and audio features that complement each other. Multimodality is defined by analyzing more than one modality, Multimodal Sentiment Analysis refers to the combination of two or more input models in order to improve the performance of the analysis; a combination of text and audio-visual inputs is an example. The automatic analysis of multimodal opinion involves a deep understanding of natural languages, audio and video processing, whereas researchers are continuing to improve them. This paper focuses on multimodal sentiment analysis as text, audio and video, by giving a complete image of it and related dataset available and providing brief details for each type, in addition to that present the recent trend of researches in the multimodal sentiment analysis and its related fields will be explored.


© 2018 Yahia Hasan Jazyah and Intisar O. Hussien. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.