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Jeannette Paschen, Leyland Pitt, Jan Kietzmann, Amir Dabirian and Mana Farshid
Online brand communities provide a wealth of insights about how consumers perceive and talk about a brand, rather than what the firm communicates about the brand. The…
Online brand communities provide a wealth of insights about how consumers perceive and talk about a brand, rather than what the firm communicates about the brand. The purpose of this paper is to understand whether the brand personality of an online brand community, rather than of the brand itself, can be deduced from the online communication within that brand community.
The paper is empirical in nature. The authors use community-generated content from eight online brand communities and perform content analysis using the text analysis software Diction. The authors employ the five brand personality dictionaries (competence, excitement, ruggedness, sincerity and sophistication) from the Pitt et al. (2007) dictionary source as the basis for the authors’ analysis.
The paper offers two main contributions. First, it identifies two types of communities: those focusing on solving functional problems that consumers might encounter with a firm’s offering and those focusing on broader engagement with the brand. Second, the study serves as a blueprint that marketers can adopt to analyze online brand communities using a computerized approach. Such a blueprint is beneficial not only to analyze a firm’s own online brand community but also that of competitors, thus providing insights into how their brand stacks up against competitor brands.
This is the first paper examining the nature of online brand communities by means of computerized content analysis. The authors outline a number of areas that marketing scholars could explore further based on the authors analysis. The paper also highlights implications for marketers when establishing, managing, monitoring and analyzing online brand communities.
Julie Robson, Jillian Farquhar and Mana Farshid
Mana Farshid, Anthony Chan and Deon Nel
The rise of social media and its resultant impact on brand management has become a critical factor in guarding the reputation of the firm. Consumer‐generated content has…
The rise of social media and its resultant impact on brand management has become a critical factor in guarding the reputation of the firm. Consumer‐generated content has the potential to spread rapidly over social networks and the implications are that advertising as traditionally used by brand managers, now offers little control over the communication message. Brand managers need a better tool to gauge the changing mood in social media conversations. The purpose of this paper is to suggest a powerful method, Chernoff Faces, to compare six Sauternes wine brands based on social conversation measurement.
This study describes a source of data relating to wine brand visibility in social media, and then presents a simple yet powerful graphical tool for portraying this information. This tool facilitates the communication, understanding, and assimilation of the relevant information.
The findings of this paper are presented in six social media wine faces. Facial features are allocated to eyes, facial line, hair density and others to reflect “Social Mention” data measuring brand strength, positive and negative sentiment and related elements such passion for the brand. A brief subjective interpretation of the differences between the wine brands offers a match between Chernoff faces representation and historical data on the brands being compared.
The paper has some limitations related to the dynamic nature of social media. This study provides more of a snapshot in time rather than an ultimate set of results. Future research could be done by closely monitoring the results for a set of brands over a period. A new option to overcome this by using longitudinal data is offered as a option in future research.
Since social media are multi‐dimensional and attempts to understand conversations it requires tracking different measures simultaneously. It is important to find the best way to portray and communicate this data so that wine marketing decision makers can quickly and easily compare changes in brand images. Using faces to accomplish this is an easy and novel way compared to more demanding multidimensional scaling techniques.
Carla Ruiz-Mafe and Cleopatra Veloutsou