Quantity or quality? Comparing social media data sampling strategies for government crisis communication research

Abstract

Social media platforms are popular data sources for communication research, with X (formerly Twitter) being the most commonly used. However, strategies for high-quality social media data collection that form the cornerstone of rigorous research are rarely discussed or evaluated. In this paper, we use a case study of government crisis communication during Covid-19 in Germany and Italy to compare deductive and inductive sampling strategies on X in two different timeframes. We used different metrics (Jaccard index, precision, and recall) and different comparisons (relevant users and content, top users and terms, and tweeting frequency over time) to analyze which sampling strategy would provide high-quality data for research. Our results revealed that the deductive sampling strategy outperformed the inductive strategy in all the studied cases, this emphasizes the importance of data quality over quick access or the size of the data set. Further implications for comparative and computational research are discussed.

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