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
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10100 - Mathematics
Result continuities
Project
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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
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ISSN
1877-0509
e-ISSN
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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
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