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Making Sense of Spatial Relationships Trough Local Knowledge Discovery in Social Media

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Book cover Computational Science and Its Applications – ICCSA 2017 (ICCSA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10407))

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Abstract

Over time, theories, models and methods have used scientific knowledge and structured data to model the relationships occurring across agents and places in a variety of domains. Recently, the diffusion of Social Networks is opening new research scenarios. Huge flows of data are being made available from Social Networks which contribute to the diffusion of local knowledge and to unravel several complex system dynamics.

The present work aims at advancing the understanding of how spatial relationships embedded in natural language communications may help harness local knowledge in planning- and decision-making processes. To that purpose, we developed a pilot study on disaster response in the Metropolitan Area of Bari (Italy), by administering an on-line survey focussed on social media use in emergency situations.

Main results suggest that the correct interpretation of local knowledge-laden natural language becomes a challenging problem when the role of tacit or implicit knowledge is taken into account. We argue in favour of acknowledging the importance of local knowledge for a full understanding of spatial relationships and calls for implementing spatial data science tools in such a way that local and tacit knowledge (including vernacular forms) may be adequately understood.

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Notes

  1. 1.

    This is true in the case in which the message is sent from a device equipped with GPS and the application used to send the post is turned on. The user authorises the activation of the application.

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Author information

Authors and Affiliations

  1. Polytechnic of Bari, Via Orabona 4, 70125, Bari, Italy

    Pasquale Balena, Alessandro Bonifazi & Dino Borri

  2. ITERAS – Research Centre for Sustainability and Territorial Innovation, Via C. Colombo 40, 70126, Bari, Italy

    Alessandro Bonifazi

  3. University of Foggia, Largo Papa Giovanni Paolo II 1, 71100, Foggia, Italy

    Caterina De Lucia

Authors
  1. Pasquale Balena
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  2. Alessandro Bonifazi
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  3. Dino Borri
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  4. Caterina De Lucia
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Corresponding author

Correspondence to Pasquale Balena .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Ota, Nigeria

    Sanjay Misra

  4. University of Trieste, Trieste, Italy

    Giuseppe Borruso

  5. Polytechnic University of Bari, Bari, Italy

    Carmelo M. Torre

  6. University of Minho, Braga, Portugal

    Ana Maria A.C. Rocha

  7. Monash University, Clayton, Victoria, Australia

    David Taniar

  8. Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  9. Saint Petersburg State University, Saint Petersburg, Russia

    Elena Stankova

  10. University of Trieste, Trieste, Italy

    Alfredo Cuzzocrea

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Balena, P., Bonifazi, A., Borri, D., De Lucia, C. (2017). Making Sense of Spatial Relationships Trough Local Knowledge Discovery in Social Media. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2017. ICCSA 2017. Lecture Notes in Computer Science(), vol 10407. Springer, Cham. https://doi.org/10.1007/978-3-319-62401-3_46

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  • DOI: https://doi.org/10.1007/978-3-319-62401-3_46

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-62400-6

  • Online ISBN: 978-3-319-62401-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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