User stance prediction - Gan, Kah Ee (Nanyang Technological University, 2023)
Stance detection is defined as understanding a person's view and opinion towards a given proposition. A person can be supporting, opposing or neutral towards a proposition. The stance detection problem consists of two sub-tasks, namely stance classification and stance prediction. This dissertation will be an extension of a work done previously during my internship at Defence Science and Technology Agency, Singapore (DSTA) on stance classification. We will be extending this project to the other sub-task of stance detection, which is stance prediction. The stance prediction's main objective is to identify the stance that towards an event has not occurred yet, or is a topic that a target user's or a target group of users' have not mentioned yet based on the past texts (tweets, posts, articles, comments, etc.) that is written by them. This Final Year Project (FYP) will explore the extensiveness of our current approach on user stance prediction as well as compare its performance with another approach using a hybrid collaborative filtering framework on 2 datasets, the VAST dataset and a self-curated r/singapore Reddit dataset. We will also be performing holistic evaluations to explore their respective abilities and limitations. This study is crucial for Natural Language Processing (NLP) researchers to design more comprehensive and accurate predictors, potentially extending their capabilities to other classification tasks.