Advertisement
Published in:
2018 | OriginalPaper | Chapter
“I Can’t Wait to See This”: An Exploratory Research on Consumer Online Word-of-Mouth on Movies: An Abstract
Authors : Julia Kampani, Chris Archer-Brown, Haiming Hang
Published in: Back to the Future: Using Marketing Basics to Provide Customer Value
Publisher: Springer International Publishing
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
Abstract
The success of a movie is often determined by its opening weekend performance (Earnest, 1985; Epstein, 2005; Gong et al., 2011). Using the most effective movie advertising tool, studios release trailers early in advance aiming to build heavy pre-release buzz which will in turn drive audiences to the cinema on the opening weekend. While pre-release movie buzz has proved to be instrumental in influencing box office performance, most electronic word-of-mouth (eWOM) research on movies is limited to the quantitative measurement of WOM metrics (e.g. volume, valence) (Hennig-Thurau et al., 2015; Liu, 2006), overlooking other significant information that could offer insight on early audience perceptions.
Very recent research on the antecedents of movie WOM has identified that the combination of liking the trailer along with understanding what the movie is about increases the likelihood of viewers engaging in favourable pre-release WOM and in paying to see the movie at the cinema (Archer-Brown et al,. 2017). Focusing on the concept of understanding, this work-in-progress aims to investigate the mechanisms through which consumers draw inferences and eventually form perceptions on upcoming movies when viewing trailers.
Approximately seven million data points on wide-release movies have been collected from Twitter and YouTube since November 2015. Content analysis will be performed on the data through automated natural language processing techniques, where networks of words will be drawn as an innovative way to visualise user-generated content. Early results on the analysis of three movies suggest that viewers utilise different techniques in inference-making depending on prior knowledge about the movie. eWOM on sequel movies focuses on the appearance and on the prominence of characters, while WOM on true story adaptations is richer with debates on how events truly happened and with the provision of secondary sources of information. Finally, WOM on movies with original storylines suggests that viewers rely on heuristic cues – such as the stars’ and directors’ previous work or other same-genre movies – when trying to fill in missing information about the movie’s plot.
This is the first part of an ongoing research project which eventually aims to construct a framework for classifying comprehensive trailers and identifying their relationship to favourable WOM and to box office performance. Theoretical contributions will be made towards advertising and WOM theory, by delving deeper into a newly added WOM antecedent. Managerial contributions include the design of effectively comprehensive promotional material as well as methodologies which can be adopted to gain insight on early audience perceptions.