31st October 2020*
Applicants should contact the primary supervisor, and submit their Expression of Interest (EOI) and Application as soon as possible.
*unless filled earlier
Sentiment analysis (also known as opinion mining) refers to the use of natural language processing and text analysis to identify and extract subjective information in source materials. Sentiment analysis is widely applied to reviews and social media for a variety of applications, ranging from marketing to customer service. Sentiment analysis aims to determine the attitude of a speaker or a writer with respect to some topic or the overall contextual polarity of a document. The attitude may be his or her judgment or evaluation, affective state (the emotional state of the author when writing), or the intended emotional communication (the emotional effect the author wishes to have on the reader).
The rise of social media such as blogs and social networks has fuelled interest in sentiment analysis. With the proliferation of reviews, ratings, recommendations and other forms of online expression, online opinion has turned into a kind of virtual currency for businesses looking to market their products, identify new opportunities and manage their reputations. Companies look to automate the process of filtering out the noise, understanding the conversations, identifying the relevant content, and actioning it appropriately. This project aims at employing Machine Learning algorithms to automatically detect sentiment in user reviews of interested online business websites.
The following eligibility criteria apply to this project:
Please contact Dr Shuxiang Xu for more information.