Determination, estimation and enhancement of social media user engagement: a deep dive into sports marketing

Abstract

Enhancing user engagement on social media platforms such as Twitter is imperative for sports franchises, organizations and individual influencers because higher engagement correlates positively with better sponsorships. This dissertation focuses on improving user engagement and delves deeply into the factors that influence engagement between a fan and numerous stakeholders on Twitter. Our results emphasize the significance of a differentiated Twitter content generation strategy for sports clubs. The first essay examines the factors that enable and enhance harmonious relationships between fans and sports franchises. Through an empirical investigation of tweets on the Indian Premier League (IPL) and a survey of fans, we deduce a fandom research framework and show that even though franchises are providing fans with the content that motivate fans to follow the franchise on Twitter, more efforts are needed in terms of content generation to make these fans engage with the content. In the second essay, using the Homophily Theory in the social media domain, we conceptualize a model and investigate the influence of a perceived and an actual match between a tweeter's and a sports franchise's geo-locations on Twitter engagement. Our findings reveal that a tweet’s engagement metrics positively correlate with whether the tweeter demonstrates demographic homophily with the mentioned sports franchise or the user perceives a demographic homophily between the two. In the third essay, we propose a Deep Player Performance Index (DPPI) to evaluate a player's in-season performance. To build DPPI, we first modify the Fédération Internationale de Football Association (FIFA) performance evaluation guidelines in the context of T20 cricket. We then propose DPPI based on K-Means clustering and Random Forest algorithm. Our empirical results show that DPPI captures a player’s batting and bowling strengths better than other indexes. In the fourth essay, we utilize the DPPI results to analyze the impact of a player's performance on user engagement metrics of the player-related social media content during in-season. Our results reveal that fans’ pre-season performance expectations from a batter and a batter’s divergence from those expectations, have a significant impact on social media engagement of content generated around that player during the season.