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Detecting a citizens' activity profile of an urban territory through natural language processing of social media data

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F22%3A00130436" target="_blank" >RIV/00216224:14310/22:00130436 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1016/j.procs.2022.10.203" target="_blank" >https://doi.org/10.1016/j.procs.2022.10.203</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.procs.2022.10.203" target="_blank" >10.1016/j.procs.2022.10.203</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Detecting a citizens' activity profile of an urban territory through natural language processing of social media data

  • Original language description

    The article presents the premises, process, and outcomes of the research, devoted to investigation of the suitability of natural language processing approaches (named entity recognition and subject-predicate-object triplets’ extraction, in particular), applied to social media data, for the problem of building a profile of citizens' activity in an urban territory. Using the named entity recognition approach, supplemented with the custom method of named urban entities distillation, it was possible to build a detailed and representative list of named urban entities for the sample territory of Hatfield, Hertfordshire. Using the subject-predicate-object triplets’ extraction approach, supplemented with the custom activity description patterns, it was possible to get the picture of citizens’ activity corresponding to the identified urban entities. The outcomes were verified on the Twitter and Instagram social networks data and evaluated from the perspectives of the resulting profile quality.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10100 - Mathematics

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2022

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Procedia Computer Science

  • ISBN

  • ISSN

    1877-0509

  • e-ISSN

  • Number of pages

    12

  • Pages from-to

    11-22

  • Publisher name

    Elsevier

  • Place of publication

    Amsterdam

  • Event location

    St. Petersburg, Virtual

  • Event date

    Sep 5, 2022

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article