Emotion Analysis and Topic Modelling of Supply Chain Discussion during the COVID-19 Pandemic

Suhong Li, Fang Chen and Thomas Ngniatedema
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Suhong Li: Bryant University, Rhode Island, U.S.A.
Fang Chen: University of New Haven, Connecticut, U.S.A.
Thomas Ngniatedema: Morgan State University, Maryland, U.S.A.

American Business Review, 2025, vol. 28, issue 1, 203-222

Abstract: This study aims to investigate the supply chain discussion during the COVID-19 pandemic using the supply chain tweets collected between March 2020 and May 2022 globally. The findings reveal an evolving sentiment trajectory: while the users’ sentiment remained neutral in 2020 and 2021, a negative sentiment surged starting in January 2022. Moreover, an emotion analysis indicates a mix of sadness and optimism among Twitter users, with anger gradually intensifying from June 2021 onward. Furthermore, topic modeling reveals distinct themes discussed each year. In 2020, major topics centered around the government’s response to COVID-19, food and medical supply chain crises. By 2021, discussions shifted to inflation/gas prices, government handling of supply chain crisis, and vaccination/recovery efforts. The first half of 2022 witnessed dominant discussions on the war in Ukraine, inflation and human rights, the US election and border crossing issues. The implications of these findings were discussed at the end.

Keywords: COVID-19; Supply Chain Management; Twitter Analytics; Natural Language Processing; Topic Modelling (search for similar items in EconPapers)
JEL-codes: C50 L60 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:ris:ambsrv:0133

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