Citation

P.Ramis, Niroshaan and Ng, Kok Why and Haw, Su Cheng (2022) Spect-level Sentiment Analysis on Online Product Review. In: Postgraduate Colloquium December 2022, 1-15 December 2022, Multimedia University, Malaysia. (Unpublished)

Text 24.NIROSHAAN A-L P.RAMIS.pdf - Submitted Version Restricted to Registered users only Download (278kB)

Abstract

Covid-19 has impacted the way people shop, moving away from the traditional, conventional way of shopping to online shopping which can be done with a click on a button. Online shopping is said to be convenient, variety of products and better priced. Customers rely largely on product reviews before making purchase decision. However, product reviews can be ambiguous, sarcastic, in the form of emojis and multilingual. This makes it challenging to mine sentiments from the reviews. Hence, this project proposes an aspect-level sentiment analysis approach with lexicon-based pre-processing to mine sentiments from online product reviews. The indicators that will be used to measure the performance of the models are accuracy, precision, recall and F1-score.

Item Type:	Conference or Workshop Item (Poster)
Uncontrolled Keywords:	e-commerce
Subjects:	H Social Sciences > HF Commerce > HF5001-6182 Business > HF5546-5548.6 Office management > HF5548.32-.34 Electronic commerce
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	20 Dec 2022 01:40
Last Modified:	20 Dec 2022 01:40
URII:	http://shdl.mmu.edu.my/id/eprint/10940

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