Narrative engagement and vicarious interaction with multiple characters

Abstract

This study investigates how audience members relate to and vicariously interact with multiple characters while viewing a narrative. Under the framework of the theory of situation models, we applied a real-time thought-listing technique that incorporated Twitter and focused on three debuting TV dramas to explore how the participants followed multiple characters while watching prime-time television dramas. We examined 3,274 tweets across the three TV series and found that monitoring a greater diversity of characters is associated with an increased number of questions asked and more accurate predictions of future events. The participants who made more accurate predictions had higher narrative engagement. In addition, the participants who had more thoughts about the self tracked a greater diversity of characters and made more accurate predictions about the plot. The results are discussed in terms of the developing literature on narratives in mass communication and entertainment research.