What is the role of emotions on football fans in affecting online video virality? (Case study of Salford City FC)

Asamaoh, JSO

Abstract

Viral video marketing is an expensive process and there is limited scholarly research about what makes video content go viral. A few online communities such as football clubs are keen to explore video virality to engage their audiences. One such club is the Salford City Football Club (FC) who have sponsored this research. Consequently, this study aims to identify the key factors that drive the virality of online video content.
To answer the research questions the STEPPS model by Jonah Berger, the Social Sharing of Emotions Theory (SSET), the Social Identity Theory (SIT) and Theory of Planned Behaviour (TPB) were some of the dominant models and theories in understanding the constructs of online video virality. A predominant variable that the STEPPS and SSET highlighted is emotional response from the video viewer, and thus, was primarily used as the theoretical basis for this work.
The primary data in this thesis comprised 60 respondents, of which were 32 football fans and 28 non-football fans. The Facial expression recognition software (Noldus 6.0) was used in combination with an online self-reporting web questionnaire to understand the emotions associated with the propensity to share content. In conjunction with emotions the thesis also investigated the role of groups (I.e. football fans and non-football fans) by analysing their effect on sharing which depicted variations on how both sets of groups respond to viral video and non-viral video stimuli.
Subsequently, the following are the original contributions to knowledge:
1)The research made theoretical advancements by examining specific emotions, arousal intensity and fan group dynamic using facial expression analysis on viral video stimuli. The results from the thesis indicate that certain emotions are intrinsically viral and have a higher intention to share. The research indicated that fan group dynamics also have a direct role to play into the extent a video is shared and should be considered as an important variable. The research explored the existence of triggers which are specific events of importance that highlight the exact phase a video is most likely to be shared.
2)The research made a methodological advancement in virality studies by developing a unique method for predicting online videos in real time using emotional viewing patterns. Related studies in virality prediction uses statistical algorithms to predict virality, this research took a different approach using the emotionality elicited from viewers obtained from facial expression analysis data.
3) The research made methodological advancements in understanding which method is more concurrent for measuring users’ emotions when watching a video stimulus by comparing facial expression analysis data with self-report. The thesis concludes facial expression analysis is a more robust approach for measuring emotions however not for subjective norms like the “intention to share”.

• Thesis Type: Thesis
• Deposit Date: Aug 7, 2020
• Publicly Available Date: Aug 7, 2020
• Award Date: Jul 13, 2020