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Consumer expression in eWOM: A text mining analysis of coffee shop Google Maps reviews in the Nordic context
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School of Business |
Master's thesis
Electronic archive copy is available via Aalto Thesis Database.
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en
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76
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Abstract
Cultural context profoundly shapes electronic word-of-mouth (eWOM), yet the specific dynamics of Google Maps reviews within the Nordic region remain largely unexplored. This research examines consumer expression in the Helsinki coffee sector through an analysis of 9,644 reviews, which includes 47 languages. A mixed-method approach, consisting of primary tools like VADER sentiment analysis and LDA topic modeling, are used to interpret the data. Reviews were classified by language group and reviewer type (Expert, Local, Casual).
The results show valuable and distinct patterns. Firstly, a "criticality gap" exists where local Finnish reviewers consistently provide more critical evaluations than other international tourists. Additionally, Nordic consumers prioritize "functional" over simple visual aesthetics. This preference creates an obvious difference in evaluation between independent cafes and chain coffee shops. Also, a "sentiment asymmetry" also characterizes the data. In these instances, positive star ratings frequently mask negative textual feedback. This divergence stems from "social friction," which is defined here as the Nordic tendency toward conflict avoidance. Such cultural norms pressure consumers to maintain numerical consensus while expressing their dissatisfaction through text. The study concludes that for Nordic markets, text mining is an essential requirement, which decodes the true satisfaction behind rating scores. Findings also offer practical implications for coffee shop operators regarding service quality, atmosphere design, and reputation management in Nordic contexts.