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Emotion dataset from Indonesian public opinion

An opinion is a type of judgment or a person's point of view about something. Twitter is a popular social media platform that includes a lot of public opinions and would be a suitable location to mine data in text form. With its vast population and active Twitter user base, Indonesia has the po...

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Detalles Bibliográficos
Autores principales: Riccosan, Saputra, Karen Etania, Pratama, Galih Dea, Chowanda, Andry
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9309654/
https://www.ncbi.nlm.nih.gov/pubmed/35898858
http://dx.doi.org/10.1016/j.dib.2022.108465
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author Riccosan
Saputra, Karen Etania
Pratama, Galih Dea
Chowanda, Andry
author_facet Riccosan
Saputra, Karen Etania
Pratama, Galih Dea
Chowanda, Andry
author_sort Riccosan
collection PubMed
description An opinion is a type of judgment or a person's point of view about something. Twitter is a popular social media platform that includes a lot of public opinions and would be a suitable location to mine data in text form. With its vast population and active Twitter user base, Indonesia has the potential to be a source of opinion data mining. An opinion may be processed and result in the form of a person's emotional response towards something, such as whether they like, hate, love, or are happy about it. Upon that basis, a dataset of Indonesian-language tweets conveying public opinion on various topics was formed. The fact that there are only limited publicly available emotions text datasets in the Indonesian language supports our basis in this research to form our emotion dataset. The gathered data was cleaned and normalized in the pre-processing stage to the necessary form for study on the task of classifying emotions in Indonesian. The data collected is annotated with six emotional labels: anger, fear, joy, love, sad, and neutral.
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spelling pubmed-93096542022-07-26 Emotion dataset from Indonesian public opinion Riccosan Saputra, Karen Etania Pratama, Galih Dea Chowanda, Andry Data Brief Data Article An opinion is a type of judgment or a person's point of view about something. Twitter is a popular social media platform that includes a lot of public opinions and would be a suitable location to mine data in text form. With its vast population and active Twitter user base, Indonesia has the potential to be a source of opinion data mining. An opinion may be processed and result in the form of a person's emotional response towards something, such as whether they like, hate, love, or are happy about it. Upon that basis, a dataset of Indonesian-language tweets conveying public opinion on various topics was formed. The fact that there are only limited publicly available emotions text datasets in the Indonesian language supports our basis in this research to form our emotion dataset. The gathered data was cleaned and normalized in the pre-processing stage to the necessary form for study on the task of classifying emotions in Indonesian. The data collected is annotated with six emotional labels: anger, fear, joy, love, sad, and neutral. Elsevier 2022-07-12 /pmc/articles/PMC9309654/ /pubmed/35898858 http://dx.doi.org/10.1016/j.dib.2022.108465 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Riccosan
Saputra, Karen Etania
Pratama, Galih Dea
Chowanda, Andry
Emotion dataset from Indonesian public opinion
title Emotion dataset from Indonesian public opinion
title_full Emotion dataset from Indonesian public opinion
title_fullStr Emotion dataset from Indonesian public opinion
title_full_unstemmed Emotion dataset from Indonesian public opinion
title_short Emotion dataset from Indonesian public opinion
title_sort emotion dataset from indonesian public opinion
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9309654/
https://www.ncbi.nlm.nih.gov/pubmed/35898858
http://dx.doi.org/10.1016/j.dib.2022.108465
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