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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Online Access: | https://dx.doi.org/10.5281/zenodo.5918507 https://zenodo.org/record/5918507 |
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ftdatacite:10.5281/zenodo.5918507 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.5918507 https://zenodo.org/record/5918507 unknown Zenodo https://dx.doi.org/10.5281/zenodo.5918508 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.5918507 https://doi.org/10.5281/zenodo.5918508 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 |
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Open Polar |
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DataCite Metadata Store (German National Library of Science and Technology) |
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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.5918507 https://zenodo.org/record/5918507 |
geographic |
Norway |
geographic_facet |
Norway |
genre |
Iceland |
genre_facet |
Iceland |
op_relation |
https://dx.doi.org/10.5281/zenodo.5918508 |
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.5918507 https://doi.org/10.5281/zenodo.5918508 |
_version_ |
1766040960252248064 |