Engaging with TV events on Twitter

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.

Social TV and audience engagement: investigating the relationship between Facebook engagement and TV performance of The Voice (USA)

“…(2015), video posts on Twitter were negatively correlated with TV show ratings. Similarly, Segijn et al. (2019) also found a negative relationship between Twitter posts and TV rating.…”

“…Conversely, according to Min et al (2015), video posts on Twitter were negatively correlated with TV show ratings. Similarly, Segijn et al (2019) also found a negative relationship between Twitter posts and TV rating. In addition, research on social TV messages has mostly focused on the use of Twitter (e.g.…”

“…Most related studies have focused on the use of Twitter (e.g. Segijn et al, 2019). Some studies have revealed that social TV viewing is positively related to the network loyalty of the audience (Lin et al, 2018), satisfaction with the show (Lin et al, 2016) and TV show ratings (Cheng et al, 2015;Cheng et al, 2016;Oh et al, 2015;Wang, 2016).…”

How Many Tweets Describe the Topics on TV Programs: An Investigation on the Relation between Twitter and Mass Media

“…However, our study is at the macro-level, which attempted to determine the relationship between social media and mass media in comprehensive trend movements. Segijn et al conducted an empirical study on the relationship between TV consumption and Twitter content [12]. They developed a vector auto regression (VAR) model for Twitter posts and TV viewing and collected data on live music event broadcasts to confirm the validity of the model.…”

Untitled

“…Among the methods of studying online consumer behaviour, the predominant ones measured are through so-called online engagement metrics, including the number of users, click-through rates, page views, content likes and comments, depending on the platform (Muñoz-Expósito et al, 2017). It is also possible to take as a basis the motivation of the individual resulting from their experience with the object, manifested in object behaviour, and viewer engagement understood as the attitude towards the brand in terms of likes, comments and shares (Segijn et al, 2019). This approach will be the basis for this article.…”