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Differential Analysis of Age, Gender, Race, Sentiment, and Emotion in Substance Use Discourse on Twitter During the COVID-19 Pandemic: A Natural Language Processing Approach

Differential Analysis of Age, Gender, Race, Sentiment, and Emotion in Substance Use Discourse on Twitter During the COVID-19 Pandemic: A Natural Language Processing Approach

The successive validation on the sample data is also presented in the study by Maharjan et al [37]. The entire workflow for data collection, preprocessing, and SU identification is depicted in step 1 of Figure 1. This comprehensive phase concluded with 2.8 million, 3.5 million, and 2.5 million SU posts identified for the years 2019, 2020, and 2021, respectively, which we used in this study. Data mining constitutes a critical initial phase for conducting this research.

Julina Maharjan, Ruoming Jin, Jennifer King, Jianfeng Zhu, Deric Kenne

JMIR Infodemiology 2025;5:e67333