Vaccine hesitancy is one of the significant obstacles to eradicating COVID-19 and putting humanity back on track. In my thesis, I analyzed the (de)motivating topics and their relation to the public stance toward the COVID-19 vaccine. This visualization approach may help us understand the relation between resonating topics on social media that are (de)motivating the public and help the healthcare workers to address them accordingly.
The data contains CSV files with anonymized user names, tweet texts, vaccine stance, cumulative score for the vaccine stance, location, and topic information. The file named all_predicted_cumulative_stance.csv contains all the tweets, scores, and classifications. We have broken this file into two separate files named demotivate_cumulative_stance.csv and motivate_cumulative_stance.csv, containing the demotivating and motivating tweets, respectively. These two files are used for the visualization.
The related paper for this work is available here.
A. Rahman and H. Alhoori, "Visualizing Relation Between (De)Motivating Topics and Public Stance Toward COVID-19 Vaccine,"
2023 ACM/IEEE Joint Conference on Digital Libraries (JCDL), Santa Fe, NM, USA, 2023, pp. 299-300,
doi: 10.1109/JCDL57899.2023.00067.