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Twitter-aided decision making: a review of recent developments

Twitter is one of the largest online platforms where people exchange information. In the first few years since its emergence, researchers have been exploring ways to use Twitter data in various decision making scenarios, and have shown promising results. In this review, we examine 28 newer papers pu...

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Detalles Bibliográficos
Autores principales: Zhang, Yihong, Shirakawa, Masumi, Wang, Yuanyuan, Li, Zhi, Hara, Takahiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8881980/
https://www.ncbi.nlm.nih.gov/pubmed/35250174
http://dx.doi.org/10.1007/s10489-022-03241-9
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author Zhang, Yihong
Shirakawa, Masumi
Wang, Yuanyuan
Li, Zhi
Hara, Takahiro
author_facet Zhang, Yihong
Shirakawa, Masumi
Wang, Yuanyuan
Li, Zhi
Hara, Takahiro
author_sort Zhang, Yihong
collection PubMed
description Twitter is one of the largest online platforms where people exchange information. In the first few years since its emergence, researchers have been exploring ways to use Twitter data in various decision making scenarios, and have shown promising results. In this review, we examine 28 newer papers published in last five years (since 2016) that continued to advance Twitter-aided decision making. The application scenarios we cover include product sales prediction, stock selection, crime prevention, epidemic tracking, and traffic monitoring. We first discuss the findings presented in these papers, that is how much decision making performance has been improved with the help of Twitter data. Then we offer a methodological analysis that considers four aspects of methods used in these papers, including problem formulation, solution, Twitter feature, and information transformation. This methodological analysis aims to enable researchers and decision makers to see the applicability of Twitter-aided methods in different application domains or platforms.
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spelling pubmed-88819802022-02-28 Twitter-aided decision making: a review of recent developments Zhang, Yihong Shirakawa, Masumi Wang, Yuanyuan Li, Zhi Hara, Takahiro Appl Intell (Dordr) Article Twitter is one of the largest online platforms where people exchange information. In the first few years since its emergence, researchers have been exploring ways to use Twitter data in various decision making scenarios, and have shown promising results. In this review, we examine 28 newer papers published in last five years (since 2016) that continued to advance Twitter-aided decision making. The application scenarios we cover include product sales prediction, stock selection, crime prevention, epidemic tracking, and traffic monitoring. We first discuss the findings presented in these papers, that is how much decision making performance has been improved with the help of Twitter data. Then we offer a methodological analysis that considers four aspects of methods used in these papers, including problem formulation, solution, Twitter feature, and information transformation. This methodological analysis aims to enable researchers and decision makers to see the applicability of Twitter-aided methods in different application domains or platforms. Springer US 2022-02-26 2022 /pmc/articles/PMC8881980/ /pubmed/35250174 http://dx.doi.org/10.1007/s10489-022-03241-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Zhang, Yihong
Shirakawa, Masumi
Wang, Yuanyuan
Li, Zhi
Hara, Takahiro
Twitter-aided decision making: a review of recent developments
title Twitter-aided decision making: a review of recent developments
title_full Twitter-aided decision making: a review of recent developments
title_fullStr Twitter-aided decision making: a review of recent developments
title_full_unstemmed Twitter-aided decision making: a review of recent developments
title_short Twitter-aided decision making: a review of recent developments
title_sort twitter-aided decision making: a review of recent developments
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8881980/
https://www.ncbi.nlm.nih.gov/pubmed/35250174
http://dx.doi.org/10.1007/s10489-022-03241-9
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