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Sentiment Analysis on Twitter-Based Teleworking in a Post-Pandemic COVID-19 Context

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  • Joan Sebastián Rojas Rincón

    (School of Administrative, Accounting, Economic and Business Sciences, Universidad Nacional Abierta y a Distancia—UNAD, Bogotá 111511, Colombia)

  • Andrés Ricardo Riveros Tarazona

    (School of Administrative, Accounting, Economic and Business Sciences, Universidad Nacional Abierta y a Distancia—UNAD, Bogotá 111511, Colombia)

  • Andrés Mauricio Mejía Martínez

    (School of Administrative, Accounting, Economic and Business Sciences, Universidad Nacional Abierta y a Distancia—UNAD, Bogotá 111511, Colombia)

  • Julio César Acosta-Prado

    (Department of Engineering, Pontificia Universidad Católica de Peru, San Miguel, Lima 15088, Peru)

Abstract

The implementation of the telework model has become popular globally due to the COVID-19 pandemic. However, this new model of work organization generates conflicting opinions regarding the positive and negative effects that its implementation can bring to organizations. In this study, sentiment analysis of Twitter-based teleworking in a post-pandemic COVID-19 context was conducted. A set of Twitter conversations is examined by applying text mining and opinion analysis techniques. The results show the prevalence of positive sentiments regarding telework. In addition, opinions are generally associated with confidence, anticipation, and joy. According to the results, it is recommended to consider telework as an opportunity to improve worker well-being. However, it is important to consider some factors, such as the sector to which the company belongs, the characteristics of the job, and the working conditions.

Suggested Citation

  • Joan Sebastián Rojas Rincón & Andrés Ricardo Riveros Tarazona & Andrés Mauricio Mejía Martínez & Julio César Acosta-Prado, 2023. "Sentiment Analysis on Twitter-Based Teleworking in a Post-Pandemic COVID-19 Context," Social Sciences, MDPI, vol. 12(11), pages 1-22, November.
  • Handle: RePEc:gam:jscscx:v:12:y:2023:i:11:p:623-:d:1276555
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    References listed on IDEAS

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    1. Tian Yan & Fang Liu, 2024. "Has sentiment returned to the pre-pandemic level? A sentiment analysis using U.S. college subreddit data from 2019 to 2022," PLOS ONE, Public Library of Science, vol. 19(3), pages 1-15, March.

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