Decoding User-Generated Images as a New Genre of eWOM: An Abstract

Abstract

The mechanism of electronic word-of-mouth (eWOM) has evolved into an omnichannel phenomenon, given the crossover between the online and offline domains where consumers share information and experiences being evident. That is, displaying a hashtag within a television advert for the purpose of driving digital consumer engagement has become common marketing practice in the field. Social media in this case have been acknowledged as a channel where eWOM occurs, both for its generation and dissemination. Instagram, as a visually-rich social media platform, portrays a socio-cultural construction of consumption through user-generated content seen as collective narratives of life experience. eWOM, contextualising within the communicative domain of Instagram, can thus be considered as syntactical visual imagery, a branch of visual semiotics in which meanings are produced, conveyed, interpreted, and represented. Despite eWOM research becoming mature, the omnichannel phenomenon of visual eWOM has yet been fully investigated and thus warrant deeper exploration. This paper aims to explore the typological characteristics of user-generated imagery in response to hashtags embedded within television advertisements, and to analyse the social semiotics of these visual postings on Instagram. Given the research aim proposed above, this study employs a social semiotic analysis of visual eWOM. Semiology provides a qualitative analytical lens to approach the production of the signs and symbols in a systematic manner and thus allows this research to identify the socio-cultural construction of meanings that are implicitly referred to by the use-generated images. John Lewis Christmas advert 2017 is chosen as the focus of this research, given it being one of the most high-profile television adverts of the year in retailing. A total of 4901 images available in the public domain are identified with the hashtag #mozthemonster, which matches the one displayed at the end of the television advert. The analysis involves an iterative process of thematic coding for semiotic data, with emphasis on identifying the typological characteristics of the collected images. The initial coding of the result outlines a preliminary framework of visual eWOM genres derived from classifying the semiotic narratives expressed in user-generated imagery. The findings suggest that projectionism and anthropomorphism are the dominating genre types that capture the combined effect of intimacy and attachment connecting the advertising object and the consumers posting the images. It is evident that visual eWOM evokes emotions through the semiotic cues embedded within the user-generated imagery. User-generated images thus can be considered as a possible new genre of eWOM whilst the visually-rich social media platform like Instagram can be seen as a vehicle of eWOM representing a socio-cultural construction of emotional brand attachment orchestrated by an omnichannel marketing approach.