Multilingual MigrationsKB: A Mulitlingual Knowledge Base of Migration related annotated Tweets

Multilingual MigrationskB (MGKB) is a mulitlingual extended version of English MGKB. The tweets geotagged with Geo location from 32 European Countries ( Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania,...

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Main Author: Yiyi Chen
Format: Dataset
Language:unknown
Published: Zenodo 2022
Subjects:
Online Access:https://dx.doi.org/10.5281/zenodo.5918508
https://zenodo.org/record/5918508
id ftdatacite:10.5281/zenodo.5918508
record_format openpolar
spelling ftdatacite:10.5281/zenodo.5918508 2023-05-15T16:50:50+02:00 Multilingual MigrationsKB: A Mulitlingual Knowledge Base of Migration related annotated Tweets Yiyi Chen 2022 https://dx.doi.org/10.5281/zenodo.5918508 https://zenodo.org/record/5918508 unknown Zenodo https://dx.doi.org/10.5281/zenodo.5918507 Open Access Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 info:eu-repo/semantics/openAccess CC-BY Dataset dataset 2022 ftdatacite https://doi.org/10.5281/zenodo.5918508 https://doi.org/10.5281/zenodo.5918507 2022-02-09T14:10:46Z Multilingual MigrationskB (MGKB) is a mulitlingual extended version of English MGKB. The tweets geotagged with Geo location from 32 European Countries ( Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, Iceland, Liechtenstein, Norway, Switzerland, the United Kingdom ) are extracted and filtered by 11 languages ( English, French, Finnish, German, Greek, Dutch, Hungarian, Italian, Polish, Spain, Swedish ). Metadata information about the tweets, such as Geo information (place name, coordinates, country code) are included. MGKB contains sentiments, offensive and hate speeches, topics, hashtags, user mentions in RDF format. The schema of MGKB is an extension of TweetsKB for migration related information. Moreover, to associate and represent the potential economic and social factors driving the migration flows, the data from Eurostat and FIBO ontology was used. To represent multilinguality, the CIDOC Conceptual Reference Model (CIDOC-CRM) is used. The extracted economic indicators, i.e., GDP Growth Rate, Total Unemployment Rate, Youth Unemployment Rate, Long-term Unemployment Rate and Income per househould, are connected with each tweet in RDF using geographical and temporal dimensions. For this version, the Multilingual MGKB is delivered separated by year. The extracted topic words are also published. Code: https://github.com/migrationsKB/MRL Please contact Yiyi Chen (yiyi.chen@partner.kit.edu) for pretrained models (Sentiment analysis/hate speech detection/ETM) if necessary. Dataset Iceland DataCite Metadata Store (German National Library of Science and Technology) Norway
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
description Multilingual MigrationskB (MGKB) is a mulitlingual extended version of English MGKB. The tweets geotagged with Geo location from 32 European Countries ( Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, Iceland, Liechtenstein, Norway, Switzerland, the United Kingdom ) are extracted and filtered by 11 languages ( English, French, Finnish, German, Greek, Dutch, Hungarian, Italian, Polish, Spain, Swedish ). Metadata information about the tweets, such as Geo information (place name, coordinates, country code) are included. MGKB contains sentiments, offensive and hate speeches, topics, hashtags, user mentions in RDF format. The schema of MGKB is an extension of TweetsKB for migration related information. Moreover, to associate and represent the potential economic and social factors driving the migration flows, the data from Eurostat and FIBO ontology was used. To represent multilinguality, the CIDOC Conceptual Reference Model (CIDOC-CRM) is used. The extracted economic indicators, i.e., GDP Growth Rate, Total Unemployment Rate, Youth Unemployment Rate, Long-term Unemployment Rate and Income per househould, are connected with each tweet in RDF using geographical and temporal dimensions. For this version, the Multilingual MGKB is delivered separated by year. The extracted topic words are also published. Code: https://github.com/migrationsKB/MRL Please contact Yiyi Chen (yiyi.chen@partner.kit.edu) for pretrained models (Sentiment analysis/hate speech detection/ETM) if necessary.
format Dataset
author Yiyi Chen
spellingShingle Yiyi Chen
Multilingual MigrationsKB: A Mulitlingual Knowledge Base of Migration related annotated Tweets
author_facet Yiyi Chen
author_sort Yiyi Chen
title Multilingual MigrationsKB: A Mulitlingual Knowledge Base of Migration related annotated Tweets
title_short Multilingual MigrationsKB: A Mulitlingual Knowledge Base of Migration related annotated Tweets
title_full Multilingual MigrationsKB: A Mulitlingual Knowledge Base of Migration related annotated Tweets
title_fullStr Multilingual MigrationsKB: A Mulitlingual Knowledge Base of Migration related annotated Tweets
title_full_unstemmed Multilingual MigrationsKB: A Mulitlingual Knowledge Base of Migration related annotated Tweets
title_sort multilingual migrationskb: a mulitlingual knowledge base of migration related annotated tweets
publisher Zenodo
publishDate 2022
url https://dx.doi.org/10.5281/zenodo.5918508
https://zenodo.org/record/5918508
geographic Norway
geographic_facet Norway
genre Iceland
genre_facet Iceland
op_relation https://dx.doi.org/10.5281/zenodo.5918507
op_rights Open Access
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
cc-by-4.0
info:eu-repo/semantics/openAccess
op_rightsnorm CC-BY
op_doi https://doi.org/10.5281/zenodo.5918508
https://doi.org/10.5281/zenodo.5918507
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