Twitter sentiment analysis for COVID-19 associated mucormycosis

Area of Science:

• Public Health
• Social Media Analysis
• Infectious Diseases

Background:

• COVID-19-associated mucormycosis (CAM) emerged as a significant public health concern during India's second COVID-19 wave.
• Understanding public perception is crucial for managing health crises.

Purpose of the Study:

• To analyze public perceptions of CAM using sentiment analysis of Twitter data.
• To gauge public emotional responses and information dissemination regarding CAM.

Main Methods:

• Observational study utilizing Twitter API to extract real-time conversations from May 3 to August 29, 2021.
• Keywords related to mucormycosis (black fungus) were used for data collection.
• Lexicon-based sentiment analysis performed using Vader, with a custom algorithm to label user sentiment.

Main Results:

• A total of 401,037 tweets were collected, with a peak frequency of 160,000 tweets between May 17-23, 2021.
• Positive sentiment tweets were more prevalent than negative ones, showing weekly variations.
• Temporal analysis indicated high initial demand for information, decreasing over time, linked to resource availability.

Conclusions:

• Social media serves as a vital platform for expressing emotions during the COVID-19 pandemic.
• A reduction in negative sentiment tweets over time suggests evolving public discourse.
• Network analysis indicated user connectivity, suggesting that such health issues can unite society.