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

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10100 - Mathematics

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2022

Kód důvěrnosti údajů

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

Název statě ve sborníku

Procedia Computer Science

ISBN

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ISSN

1877-0509

e-ISSN

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Počet stran výsledku

12

Strana od-do

11-22

Název nakladatele

Elsevier

Místo vydání

Amsterdam

Místo konání akce

St. Petersburg, Virtual

Datum konání akce

5. 9. 2022

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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