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@inproceedings{2267006,
author = {Tikhonova, Olga and Antonov, Aleksandr and Bogomolov, Jura and Khulbe, Devashish and Sobolevsky, Stanislav},
address = {Amsterdam},
booktitle = {Procedia Computer Science},
doi = {http://dx.doi.org/10.1016/j.procs.2022.10.203},
editor = {Boukhanovsky A., Krzhizhanovskaya V., Klimova A.},
keywords = {urban data analysis; social networks; Natural Language Processing (NLP); Named Entity Recognition; Classification (NERC); Subject-Predicate-Object (SPO) triplets’ extraction},
howpublished = {tištěná verze "print"},
language = {eng},
location = {Amsterdam},
note = {Bude zaindexováno na WoS. Doplnit a poté vykázat do RIV.},
pages = {11-22},
publisher = {Elsevier},
title = {Detecting a citizens' activity profile of an urban territory through natural language processing of social media data},
url = {https://doi.org/10.1016/j.procs.2022.10.203},
year = {2022}
}
TY - JOUR
ID - 2267006
AU - Tikhonova, Olga - Antonov, Aleksandr - Bogomolov, Jura - Khulbe, Devashish - Sobolevsky, Stanislav
PY - 2022
TI - Detecting a citizens' activity profile of an urban territory through natural language processing of social media data
PB - Elsevier
CY - Amsterdam
N1 - Bude zaindexováno na WoS. Doplnit a poté vykázat do RIV.
KW - urban data analysis
KW - social networks
KW - Natural Language Processing (NLP)
KW - Named Entity Recognition
KW - Classification (NERC)
KW - Subject-Predicate-Object (SPO) triplets’ extraction
UR - https://doi.org/10.1016/j.procs.2022.10.203
N2 - 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.
ER -
TIKHONOVA, Olga, Aleksandr ANTONOV, Jura BOGOMOLOV, Devashish KHULBE a Stanislav SOBOLEVSKY. Detecting a citizens' activity profile of an urban territory through natural language processing of social media data. In Boukhanovsky A., Krzhizhanovskaya V., Klimova A. \textit{Procedia Computer Science}. Amsterdam: Elsevier, 2022, s.~11-22. ISSN~1877-0509. Dostupné z: https://dx.doi.org/10.1016/j.procs.2022.10.203.
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