Exploring SNS as a consumer tool for retail therapy: explicating semantic networks of "shopping makes me happy (unhappy)" as a new product development method

Eunju Ko, Eunha Chun, Sangah Song and Pekka Mattila

Journal of Global Scholars of Marketing Science, 2015, vol. 25, issue 1, 37-48

Abstract: Marketing and advertising researchers are turning attention to the impact of social network services such as Twitter. Researchers are calling for more useful gathering and interpretation of massive amounts of SNS data. This study applies semantic network analysis to examine the effects of shopping on mood alleviation via tweets - effects known as retail therapy . To conduct a semantic network analysis, the study analyzes 152 messages containing shopping-related keywords in naturally occurring tweets and finds the 24 most frequently used nodes (keywords). Centrality analysis reveals that nodes most frequently connecting keywords of mood, stress, depression, happiness, clothes, consumption and shoes have higher degrees of centrality. Moods associate with 22 keywords and highly co-occur with the keywords change, clothes, stress, consumption and depression. The results indicate that tweets about sentiments expressed before and after fashion item purchases show that retail therapy is occurring. By analyzing SNS messages, this study enhances the theory-method diversification of consumer studies and provides practical guidelines for further study of shopping behaviors and future new product development initiatives.

Date: 2015
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Citations: View citations in EconPapers (3)

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DOI: 10.1080/21639159.2014.984891

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