Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/74875
Title: dOMiNiuM PubliCuM : opinion mining of news portal comments
Authors: Spiteri, Jean Claude (2019)
Keywords: News Web sites -- Malta
Times of Malta
Mass media and public opinion -- Malta
Sentiment analysis -- Malta
Issue Date: 2019
Citation: Spiteri, J.C. (2019). dOMiNiuM PubliCuM: opinion mining of news portal comments (Bachelor's dissertation).
Abstract: Sentiment analysis is a research problem with great potential, given the enormous applications of being able to accurately summarise the opinion expressed by a person towards any topic. It has seen a lot of research into product reviews over the years, unfortunately research into sentiment analysis on more ambiguous data like news portal comments has been far more limited due to greater challenges. We propose a rules-based aspect level sentiment analysis using an opinion word corpus to detect the sentiment expressed towards entities in user-generated content, noted to be one of the more complex forms of data. The system is designed to use comments extracted from the Times of Malta news portal. Following the extraction of comments each sentence is processed to identify if it is in English or not to ensure that only English sentences are processed further. Sentences not in the English language are simply marked and stored. The English sentences within a comment are each processed for sentiment analysis. The scores from each sentence contribute to the sentiment mean value of each entity in the specific comment. Experimental results indicate that this approach looks promising for similar endeavours in the future.
Description: B.SC.ICT(HONS)ARTIFICIAL INTELLIGENCE
URI: https://www.um.edu.mt/library/oar/handle/123456789/74875
Appears in Collections:Dissertations - FacICT - 2019
Dissertations - FacICTAI - 2019

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