1/1/2023 0 Comments Waves paz analyzer crackersA regression technique based on Random forest was used to predict the rating of an advertisement using EEG data. Textual contents from review comments were analyzed to obtain a score to understand sentiment nature of the video. Furthermore, the multimedia data that comprised of the comments posted by global viewers, were retrieved and processed using Natural Language Processing (NLP) technique for sentiment analysis. A higher valence corresponds to intrinsic attractiveness of the user. Valence scores were obtained using self-report for each video. In our framework, the users were asked to watch the video-advertisement and simultaneously EEG signals were recorded. We have fused Electroencephalogram (EEG) waves of user and corresponding global textual comments of the video to understand the user’s preference more precisely. This paper presents a novel approach to predict rating of video-advertisements based on a multimodal framework combining physiological analysis of the user and global sentiment-rating available on the internet.
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