Engaging with TV events on Twitter: The interrelations between TV consumption, engagement actors, and engagement content. Issue 2 (6th August 2019) - Segijn, Claire Monique; Maslowska, Ewa; Araujo, Theo; Viswanathan, Vijay
Abstract : Purpose: The purpose of this paper is to explore the interrelationship between television (TV) consumption (viewing ratings), engagement behaviors of different actors on Twitter (TV programs, media, celebrities and viewers) and the content of engagement behaviors (affective, program-related and social content). Design/methodology/approach: TV ratings and Twitter data were obtained. The content of tweets was analyzed by means of a sentiment analysis. A vector auto regression model was used to understand the interrelationship between tweets of different actors and TV consumption. Findings: First, the results showed a negative interrelationship between TV viewing and viewers' tweeting behavior. Second, tweets by celebrities and media exhibited similar patterns and were both affected mostly by the number of tweets by viewers. Finally, the content of tweets matters. Affective tweets positively relate to TV viewing, and program-related and social content positively relates to the number of tweets by viewers. Research limitations/implications: The findings help us understand the online engagement ecosystem and provide insights into drivers of TV consumption and online engagement of different actors. Practical implications: The results indicate that content producers may want to focus on stimulating affective conversations on Twitter to trigger more online and offline engagement. The results also call for rethinking the meaning of TV metrics. Originality/value: While some studies have explored viewer interactions on Twitter, only a few studies have looked at the effects of such interactions on variables outside of social media, such as TV consumption. Moreover, the authors study the interrelations between Twitter interactions with TV consumption, which allows us to examine the effect of online engagement on offline behaviors and vice versa. Finally, the authors take different actors into account when studying real-life online engagement.