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dc.contributor.authorLim, Shaun Wei Minen_US
dc.description.abstractAn essential part of understanding how humans interact with one another linked with their respective personalities has always been through finding out what they are thinking about. To detect subjective information such as attitudes, opinions, tone, expression etc, sentiment analysis is used to analyze these data. With the rise of social media usage, the importance of sentiment analysis increases as well. Data scientists tend to seek out the opinions of others to detect feelings based on specific events or occurrences due to the ever-expanding importance of improving business and society in the 21st century. The views of users are centered among interactions and activities with one another, which are critical influencers of our behavior. The purpose of this project is to investigate the sentiments of users’ comments in Singapore subreddit on a daily basis, plotted on an interactive dashboard that allows researchers to view the public’s sentiments for a particular day. This is achieved using Reddit web APIs, MySQL database and Chart.js plotting library. The sentiment analysis is done on the backend, which consists of NLP cleaning methods and NLTK Vadar Sentiment Analyzer. Thereafter, the paper focused on using users’ comments to generate new unseen text prior to retrieving their sentiment values. This is achieved by training the model using GPT-2 and Markov Chain. The final result shows that GPT-2 has a better result in generating new comments based on the user’s way of talking and his sentiments. These generated data can be used as fake reviews, comments etc. in the online world.en_US
dc.publisherNanyang Technological Universityen_US
dc.subjectEngineering::Computer science and engineeringen_US
dc.titleTopic extraction and sentiment analysis of subreddit - /r/Singaporeen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorAnwitaman Dattaen_US
dc.contributor.schoolSchool of Computer Science and Engineeringen_US
dc.description.degreeBachelor of Engineering (Computer Science)en_US
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Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)
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