Predicting sports fans’ engagement with culturally aligned social media content: A language expectancy perspective

Abstract

There is limited research showing how strategically generated content can boost Twitter engagement. The problem is acute for sports clubs with large fan bases. We determine the ideal content generation strategy using Hofstede’s Cultural Dimensions and Language Expectancy theory. This study examines whether culturally aligned tweets can improve fan engagement. Using tweets from a sports league, we demonstrate that culturally aligned features may be used to build machine learning and deep learning models that predict a tweet’s engagement level. According to our research, culture-specific social media content that meet fans’ language expectations can increase Twitter engagement.