User stance prediction

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 dissert...

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Main Author: Gan, Kah Ee
Other Authors: Smitha Kavallur Pisharath Gopi
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2023
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Online Access:https://hdl.handle.net/10356/166230
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Institution: Nanyang Technological University
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spelling sg-ntu-dr.10356-1662302023-05-12T15:36:49Z User stance prediction Gan, Kah Ee Smitha Kavallur Pisharath Gopi School of Computer Science and Engineering Defence Science and Technology Agency, Singapore smitha@ntu.edu.sg Engineering::Electrical and electronic engineering 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. Bachelor of Science in Data Science and Artificial Intelligence 2023-05-09T00:19:46Z 2023-05-09T00:19:46Z 2023 Final Year Project (FYP) Gan, K. E. (2023). User stance prediction. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/166230 https://hdl.handle.net/10356/166230 en SCSE22-0636 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
spellingShingle Engineering::Electrical and electronic engineering
Gan, Kah Ee
User stance prediction
description 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.
author2 Smitha Kavallur Pisharath Gopi
author_facet Smitha Kavallur Pisharath Gopi
Gan, Kah Ee
format Final Year Project
author Gan, Kah Ee
author_sort Gan, Kah Ee
title User stance prediction
title_short User stance prediction
title_full User stance prediction
title_fullStr User stance prediction
title_full_unstemmed User stance prediction
title_sort user stance prediction
publisher Nanyang Technological University
publishDate 2023
url https://hdl.handle.net/10356/166230
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