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Big Data for smart cities and citizen engagement: evidence from Twitter data analysis on Italian municipalities

Author

Listed:
  • Silvia Blasi

    (University of Verona)

  • Edoardo Gobbo

    (University of Padova)

  • Silvia Rita Sedita

    (University of Padova)

Abstract

Smart cities are increasingly keen to establish a fruitful conversation with their citizens, to better capture their needs, and create virtual platforms for stimulating co-creation processes between government and users, with the final objective of increasing the quality of life and well-being. Social media applications provide an opportunity for dialogic communication, where, for a relatively low cost, a large amount of information reaching a wide audience can be published and exchanged in real time, fueling opportunities for citizens’ engagement. This study is based on a social media listening method, through a twitter data mining, which enabled disentangling different components of citizen engagement (popularity, commitment and virality) for a sample of Italian municipalities. In addition, we executed a deep analysis of the types of communication artifact exchanged and, through a content analysis of the tweets published by followers of the municipalities’ accounts, we identified main areas of interests of the social media conversations. Our results are based on the analysis of online conversations engaged by followers of twitter accounts of a sample of 28 Italian municipalities, chosen among the most active and densely populated. We show that municipalities tend to use the twitter account as a channel of communication to inform the population about a variety of topics, such as transports and public works, among the others. The volume of activity and number of followers (audience) vary from one municipality to the other. There is generally a negative relationship between the density of the population of a municipality and citizens’ engagement: smaller municipalities show a higher citizens’ engagement; the biggest ones, like Roma, Milan, Turin, Naples, are laggards. We finally conducted a city profiling process, which provides a representation of key citizens’ segments in terms of engagement. Policy makers could find in our work useful tools to increase citizens’ listening capacity.

Suggested Citation

  • Silvia Blasi & Edoardo Gobbo & Silvia Rita Sedita, 2022. "Big Data for smart cities and citizen engagement: evidence from Twitter data analysis on Italian municipalities," Working Papers - Business wp2022_01.rdf, Universita' degli Studi di Firenze, Dipartimento di Scienze per l'Economia e l'Impresa.
  • Handle: RePEc:frz:wpmmos:wp2022_01.rdf
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    References listed on IDEAS

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    1. Neil Lee, 2019. "Inclusive Growth in cities: a sympathetic critique," Regional Studies, Taylor & Francis Journals, vol. 53(3), pages 424-434, March.
    2. Rob Kitchin, 2015. "Making sense of smart cities: addressing present shortcomings," Cambridge Journal of Regions, Economy and Society, Cambridge Political Economy Society, vol. 8(1), pages 131-136.
    3. Stephen Johnson, 1967. "Hierarchical clustering schemes," Psychometrika, Springer;The Psychometric Society, vol. 32(3), pages 241-254, September.
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    Cited by:

    1. Giovanni Baldi & Antonietta Megaro & Luca Carrubbo, 2022. "Small-Town Citizens’ Technology Acceptance of Smart and Sustainable City Development," Sustainability, MDPI, vol. 15(1), pages 1-18, December.
    2. Silvia Rita Sedita & Silvia Blasi & Jiawen Yang, 2022. "The cultural dimensions of sustainable development: A cross‐country configurational analysis," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(6), pages 1838-1849, December.

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    More about this item

    Keywords

    smart cities; e-government; twitter; web scraping; social media listening; we-government;
    All these keywords.

    JEL classification:

    • M10 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - General
    • M38 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Government Policy and Regulation

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