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https://hdl.handle.net/10356/70500
Title: | Sentiment analysis in reviews | Authors: | Abdul Rasyid Sapuan | Keywords: | DRNTU::Social sciences::Psychology::Affection and emotion DRNTU::Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence |
Issue Date: | 2017 | Abstract: | In this study, we investigate the feasibility of using self-ratings and autonomic EEG activity in classifying sentiment elicited from individuals watching truthful and deceptive videos. The alpha and beta waves of EEG activity are isolated and tested to understand the role of subconscious and conscious brain activities in discriminating between truthful and deceptive videos. Furthermore, three cortical functions: attention, emotion and memory are studied to observe the significance of the different brain processes contributing to the act of forming sentiment. The study concludes with the outlook that conditioning impedes the performance of subjects while unconditioned, inexperienced subjects performed better. Also, memory access is a factor in conditioned subjects that consistently provides their best classification results while emotion contributes similarly to the performance of unconditioned subjects. We note that EEG activity performs satisfactorily with an average accuracy of 75.4% in discriminating between truth and deceit for the inexperienced, unconditioned subjects. This then increases to 78.8% when performing the same task on a separate set of stimuli, suggesting that subjects learn from an unconditioned exposure to truth and deception. | URI: | http://hdl.handle.net/10356/70500 | Schools: | School of Computer Science and Engineering | Rights: | Nanyang Technological University | Fulltext Permission: | restricted | Fulltext Availability: | With Fulltext |
Appears in Collections: | SCSE Student Reports (FYP/IA/PA/PI) |
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File | Description | Size | Format | |
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AbdulRasyidSapuan_FYPReport_v2.pdf Restricted Access | Project Report | 11.42 MB | Adobe PDF | View/Open |
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