Topic Modeling and Sentiment Analysis of US' Afghan Exit Twitter Data: A Text Mining Approach

10.6186/IJIMS.202303_34(1).0003

Addo Prince Clement；Akpatsa Samuel Kofi；Dorgbefu Jr Maxwell；Dagadu Joshua Caleb；Tattrah Victor Dela；Dzoagbe Newton Kofi；Fiawoo Duncan Dodzi；Nartey Juliana

Twitter sentiment analysis ； Text classification ； Afghanistan ； Machine learning

International Journal of Information and Management Sciences

34卷1期（2023 / 03 / 01）

51 - 64

英文

The withdrawal of US troops from Afghanistan and the subsequent collapse of the Afghan government threatens the lives, security, and human right of many people. Twitter and other social media platforms took the lead in opinion and sentiment sharing, allowing researchers to make a real-time assessment that may help authorities develop early response strategies. In this study, 362,566 tweets relating to the exit of the US troops from Afghanistan collected between August 11 and 27, 2021, are analyzed using text mining techniques, including sentiment analysis and word cloud analysis. The analysis shows diverse topics on social media related to the fallout, and the general reaction regarding the crisis was negative.

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