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

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

Abstract

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

참고문헌 (51)

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