Building a sentiment corpus using a gamified framework

Gamification, the use of game mechanics and game elements in non-game contexts, is an emerging approach for crowdsourcing the collection of data. This study uses a gamified application in the form of an online debate game as a cost-efficient way to build an agreement-objection corpus from which a se...

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Main Author: Tiam-Lee, Thomas James
Format: text
Language:English
Published: Animo Repository 2014
Online Access:https://animorepository.dlsu.edu.ph/etd_masteral/4613
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Institution: De La Salle University
Language: English
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spelling oai:animorepository.dlsu.edu.ph:etd_masteral-114512024-04-18T08:04:00Z Building a sentiment corpus using a gamified framework Tiam-Lee, Thomas James Gamification, the use of game mechanics and game elements in non-game contexts, is an emerging approach for crowdsourcing the collection of data. This study uses a gamified application in the form of an online debate game as a cost-efficient way to build an agreement-objection corpus from which a sentiment corpus can potentially be derived. This approach has advantages over traditional ways which are difficult, time-consuming, and expensive, since there is currently no automated way to determine sentiment polarity. It allows for a time-efficient and cost-efficient way of building a sentiment corpus that can be applied to several natural language processing tasks and research. Polarity, the gamified application used for this study, was able to collect 626 statements after being deployed for 43 days. The cleaning process was able to filter out 72.88% of the noise data. After the cleaning process, a total of 596 statements remained in the agreement-objection corpus. Assuming that this corpus can be mapped into a sentiment corpus by assuming all agree statements are positive and everything else are negative, it results into a sentiment corpus of 82.86% accuracy. 2014-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/etd_masteral/4613 Master's Theses English Animo Repository
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
language English
description Gamification, the use of game mechanics and game elements in non-game contexts, is an emerging approach for crowdsourcing the collection of data. This study uses a gamified application in the form of an online debate game as a cost-efficient way to build an agreement-objection corpus from which a sentiment corpus can potentially be derived. This approach has advantages over traditional ways which are difficult, time-consuming, and expensive, since there is currently no automated way to determine sentiment polarity. It allows for a time-efficient and cost-efficient way of building a sentiment corpus that can be applied to several natural language processing tasks and research. Polarity, the gamified application used for this study, was able to collect 626 statements after being deployed for 43 days. The cleaning process was able to filter out 72.88% of the noise data. After the cleaning process, a total of 596 statements remained in the agreement-objection corpus. Assuming that this corpus can be mapped into a sentiment corpus by assuming all agree statements are positive and everything else are negative, it results into a sentiment corpus of 82.86% accuracy.
format text
author Tiam-Lee, Thomas James
spellingShingle Tiam-Lee, Thomas James
Building a sentiment corpus using a gamified framework
author_facet Tiam-Lee, Thomas James
author_sort Tiam-Lee, Thomas James
title Building a sentiment corpus using a gamified framework
title_short Building a sentiment corpus using a gamified framework
title_full Building a sentiment corpus using a gamified framework
title_fullStr Building a sentiment corpus using a gamified framework
title_full_unstemmed Building a sentiment corpus using a gamified framework
title_sort building a sentiment corpus using a gamified framework
publisher Animo Repository
publishDate 2014
url https://animorepository.dlsu.edu.ph/etd_masteral/4613
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