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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2022
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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. |
format | Online Article Text |
id | pubmed-8881980 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
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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