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A Network-Based Indicator of Travelers Performativity on Instagram

Author

Listed:
  • Giuseppe Giordano

    (University of Salerno)

  • Ilaria Primerano

    (University of Salerno)

  • Pierluigi Vitale

    (University of Salerno)

Abstract

The spread of Internet and online social media has created a huge amount of data able to provide new insights to researchers in different disciplinary fields, but it also presents new challenges for data science. Data arising from online social networks can be naturally coded as relational data in affiliation and adjacency matrices, then analyzed with social network analysis. In this study, we apply an interdisciplinary approach (based on automatic visual content analysis, social network analysis, and exploratory statistical techniques) to define and derive a suitable indicator for characterizing places, along with the online activities of travelers, in terms of sharing images. We envisage a novel storytelling perspective where stories are related to places and the narrative activity is realized through posting images. Specifically, we use data extracted from an online social network (i.e., Instagram) to identify travelers’ paths among sites of interests. Starting from a large collection of pictures geolocalized in a pre-specified set of locations (i.e., five locations in the Campania region of Italy during the 2018 Christmas season), we use automatic alternative text to produce an ex-post taxonomy of images on the most recurrent themes emerging from pictures posted on Instagram. Quantitative measures defined on the co-occurrence of locations and the emerging themes are used to build a statistical indicator able to characterize paths among different locations as narrated from travelers’ posts. The proposed analysis, presented and discussed along with real data, can be useful for stakeholders interested in the fields of policy-making, communication design, and territory profiling strategies.

Suggested Citation

  • Giuseppe Giordano & Ilaria Primerano & Pierluigi Vitale, 2021. "A Network-Based Indicator of Travelers Performativity on Instagram," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 156(2), pages 631-649, August.
    • Handle: RePEc:spr:soinre:v:156:y:2021:i:2:d:10.1007_s11205-020-02326-7
    DOI: 10.1007/s11205-020-02326-7
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    References listed on IDEAS

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    1. Estela Marine-Roig, 2017. "Measuring Destination Image through Travel Reviews in Search Engines," Sustainability, MDPI, vol. 9(8), pages 1-18, August.
    2. Kawaljeet Kaur Kapoor & Kuttimani Tamilmani & Nripendra P. Rana & Pushp Patil & Yogesh K. Dwivedi & Sridhar Nerur, 2018. "Advances in Social Media Research: Past, Present and Future," Information Systems Frontiers, Springer, vol. 20(3), pages 531-558, June.
    3. Pantano, Eleonora & Priporas, Constantinos-Vasilios & Stylos, Nikolaos, 2017. "‘You will like it!’ using open data to predict tourists' response to a tourist attraction," Tourism Management, Elsevier, vol. 60(C), pages 430-438.
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    Cited by:

    1. Vincenzo Giuseppe Genova & Giuseppe Giordano & Giancarlo Ragozini & Maria Prosperina Vitale, 2024. "An analytic strategy for data processing of multimode networks," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 18(3), pages 745-767, September.

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