Development of a sentiment corpus from a gamified approach

This paper discusses a sentiment corpus that was built from a gamified application. Each entry in the corpus contains a topic, a statement, and an annotation which tells if the statement bears a positive or negative sentiment towards the topic. These were generated from the Polarity gamified web app...

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Main Authors: Tiam-Lee, Thomas James Z., See, Solomon
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Published: Animo Repository 2010
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Online Access:https://animorepository.dlsu.edu.ph/faculty_research/7436
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Institution: De La Salle University
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spelling oai:animorepository.dlsu.edu.ph:faculty_research-80572022-10-20T05:57:56Z Development of a sentiment corpus from a gamified approach Tiam-Lee, Thomas James Z. See, Solomon This paper discusses a sentiment corpus that was built from a gamified application. Each entry in the corpus contains a topic, a statement, and an annotation which tells if the statement bears a positive or negative sentiment towards the topic. These were generated from the Polarity gamified web application. Manual evaluation of the corpus yields an 82.86% accuracy and a 90.99% inter-rater agreement, showing that there is a potential for corpora built from gamified approaches to be used in natural language processing tasks. 2010-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/faculty_research/7436 Faculty Research Work Animo Repository Sentiment analysis Natural language generation (Computer science) Computer Sciences
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
topic Sentiment analysis
Natural language generation (Computer science)
Computer Sciences
spellingShingle Sentiment analysis
Natural language generation (Computer science)
Computer Sciences
Tiam-Lee, Thomas James Z.
See, Solomon
Development of a sentiment corpus from a gamified approach
description This paper discusses a sentiment corpus that was built from a gamified application. Each entry in the corpus contains a topic, a statement, and an annotation which tells if the statement bears a positive or negative sentiment towards the topic. These were generated from the Polarity gamified web application. Manual evaluation of the corpus yields an 82.86% accuracy and a 90.99% inter-rater agreement, showing that there is a potential for corpora built from gamified approaches to be used in natural language processing tasks.
format text
author Tiam-Lee, Thomas James Z.
See, Solomon
author_facet Tiam-Lee, Thomas James Z.
See, Solomon
author_sort Tiam-Lee, Thomas James Z.
title Development of a sentiment corpus from a gamified approach
title_short Development of a sentiment corpus from a gamified approach
title_full Development of a sentiment corpus from a gamified approach
title_fullStr Development of a sentiment corpus from a gamified approach
title_full_unstemmed Development of a sentiment corpus from a gamified approach
title_sort development of a sentiment corpus from a gamified approach
publisher Animo Repository
publishDate 2010
url https://animorepository.dlsu.edu.ph/faculty_research/7436
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