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Place Marketing or Civic Information? Classifying Municipal Tweets using Machine Learning

Author

Listed:
  • Bergh, Andreas

    (Lund University and)

  • Anzén Ekman, Christina

    (Lund University)

  • Moricz, Sara

    (Sensative)

Abstract

How do municipalities use social media? For place marketing, civic information, or dialogue with citizens? We address this question by classifying 35,930 tweets from 15 municipal Twitter accounts in the Skåne region of Sweden, using a machine learning algorithm trained on manually annotated data. Tweets are classified along two dimensions: whether they contain place marketing content and whether they contain civic information, yielding four categories. Our findings show that place marketing content declined substantially over the period studied, from nearly 40 percent of tweets in 2009 to just above 20 percent in 2018. In contrast, civic information and direct dialogue with citizens increased. These results suggest that the rise of social media has not trapped municipalities in a zero-sum place marketing arms race. Instead, municipalities appeared to be using Twitter increasingly as a channel for civic communication, with implications for how scholars and practitioners understand the evolving role of social media in place branding.

Suggested Citation

  • Bergh, Andreas & Anzén Ekman, Christina & Moricz, Sara, 2026. "Place Marketing or Civic Information? Classifying Municipal Tweets using Machine Learning," Working Paper Series 1563, Research Institute of Industrial Economics.
  • Handle: RePEc:hhs:iuiwop:1563
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    JEL classification:

    • H83 - Public Economics - - Miscellaneous Issues - - - Public Administration
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • R58 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Regional Development Planning and Policy

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