leagues compete. This is achieved by adopting Ehrenberg’s ( 1971 ) well-established framework of buyer behavior within repeat-purchase markets, utilizing the negative binomial distribution (NBD) Dirichlet model of market analysis ( Bassi, 2011 ). The core research purpose therefore is to understand sport
Hunter Fujak, Stephen Frawley, Heath McDonald and Stephen Bush
Liam Kennedy, Derek Silva, Madelaine Coelho and William Cipolli III
hashtag in Figure 3 . Finally, relying on machine learning architecture and Natural Language Processing (NLP), we used latent Dirichlet allocation (LDA) to generate statistical models that help separate large bodies of text into small groups of similar topics ( Blei, Ng, & Jordan, 2003 ). This enabled us
Brian A. Eiler, Rosemary Al-Kire, Patrick C. Doyle and Heidi A. Wayment
to textual analysis than bag-of-word approaches (e.g., LIWC), other techniques such as topic modeling, latent semantic analysis, latent Dirichlet analysis, or other supervised machine learning approaches may provide more nuanced insight. Third, our research did not differentiate between different
