Leveraging market basket analysis for enhanced understanding of social media platform usage

This paper explores the application of Market Basket Analysis (MBA), a quantitative technique traditionally employed in retail environments to enhance marketing and inventory strategies, to the realm of social media usage. Recognizing the potential of MBA to reveal insightful patterns within complex datasets, this study adapts the approach to analyze interactions across diverse social media platforms, thus framing user activities on these platforms as analogous to consumer transactions in a market basket. Leveraging a dataset provided by Pew Research, which encompasses responses from adults across all 50 U.S. states, the study employs the Apriori algorithm to identify and evaluate associations between major platforms such as Facebook, Instagram, and Twitter. The analysis focuses on deriving metrics such as support, confidence, lift, and deployability to ascertain the robustness and relevance of the identified associations. The results underscore significant interconnections between user engagements across different platforms, providing empirical support for enhanced strategic decision-making by platform developers and marketers. By extending the application of MBA to the study of digital interactions, this paper not only broadens the understanding of user behavior in digital ecosystems but also enriches the methodological toolkit available for digital sociology and media studies, demonstrating the adaptability of MBA across varied analytical contexts.