Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/137984
Title: Topic extraction and sentiment analysis of subreddit - /r/Singapore
Authors: Lim, Shaun Wei Min
Keywords: Engineering::Computer science and engineering
Issue Date: 2020
Publisher: Nanyang Technological University
Project: SCSE19-0197
Abstract: An 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.
URI: https://hdl.handle.net/10356/137984
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
SCSE19-0197_FYP_FinalReport.pdf
  Restricted Access
2.77 MBAdobe PDFView/Open

Page view(s)

250
Updated on Nov 26, 2022

Download(s) 50

26
Updated on Nov 26, 2022

Google ScholarTM

Check

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.