The following research was designed to introduce CAT into a practical setting for social media managers while primarily examining Minor League Baseball (MiLB) at the Single-A level. Single-A baseball has not been examined solely in a social media setting, which was why this level of MiLB was selected. Study A was designed to measure the levels of accommodation across various posting strategies (neoliberal, social, team related, open code) and the subsequent number of likes and number of comments accompanying each post. The accommodation scores, measured through the Language Inquiry and Word Count software (LIWC, pronounced “Luke”), accompanied by a series of algorithms, and the traditional measures for traditional Facebook metrics were measured using a regression analysis. There was some evidence to suggest that number of comments was correlated to LSM scores, while various posting types were significant at the team level. Study B was designed to measure the differences between the most and least liked Single-A MiLB Facebook pages in terms of levels of accommodation. This exploration utilized regression to measure accommodation’s influence on likes and number of comments. As expected, traditional Facebook metrics such as likes and number of comments per post were higher for the team with more page likes, although accommodation scores were higher for the team with fewer page likes. The implications of these studies, and future direction for social media academics and practitioners, are also explored
