Public audiencing: Using Twitter to study audience engagement with characters and actors

Abstract

The current fascination with social media sites has undoubtedly made many parts of our lives more public. We are increasingly publicising not only our activities, relationships, and cultural preferences, but also the way we think and understand the world. These new data streams provide avenues for researchers to gather insight into both personal and public opinion and behaviour.

One particular space that has attracted scholarly attention is the live tweeting of television. As audiences discuss television shows through second screen applications, researchers have an opportunity to gain insight into the way viewers engage with elements of a media text without soliciting or directing the discussion. This public 'audiencing' has been studied in the context of Eurovision, reality television, talk shows, and news and current affairs shows, but little work has been done in the space of fictional television. Those who study tweeting of fictional shows tend to examine the audience as members of a fandom, who may demonstrate dedication to the show in excess of that expected of a casual viewer. With second screen use becoming increasingly common through a range of audience types, a wider approach is necessary to encompass a fuller range of audience behaviour.

In order to expand the focus of research into television audience use of Twitter to engage with fictional television shows, this chapter reports on a focused study of tweets relating to the first broadcast of the second season of Love Child (Nine Network, 2015). This analysis focuses specifically on how the collected tweets reference actors and characters, demonstrating that Twitter studies can make visible audience identification practices. In particular, the analysis identifies three key behavioural elements: direct address to the actors, either inside or outside the diegetic space; tagging actors while referencing character behaviour; and character bleed. Although these types of audience behaviour pre-existed the development of Twitter, studying them has been problematic due to the influence that the researcher and the research process could have on the data collection process. Analysing unsolicited data such as that discussed here provides researchers with new ways to understand audience responses to media texts.