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ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2020
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
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BreXLiMe: A Semantically Enriched Dataset With News Articles, Micro-Posts, and TV Shows Related to the Brexit

Authors: Färber, Michael;

BreXLiMe: A Semantically Enriched Dataset With News Articles, Micro-Posts, and TV Shows Related to the Brexit

Abstract

We provide a large data set of media content metadata from various media sources (including online news sites, social media, and live-TV) in three languages (English, German, and Spanish). Overall, the data set contains rich metadata for about 240 thousand news articles, 12 million micro-posts, and 900 TV shows. All media content information has been semantically enriched with annotations of both entities and categories from DBpedia. The data can be used as a valuable data basis for applications and studies of various disciplines (e.g., social studies, political science, and humanities) on the case of Brexit, particularly on the media landscape before the Brexit referendum held on June 23, 2016. We provide the data set in the RDF serialization format Turtle (.ttl) as well as in XML. If you use our data set, please cite it as follows: Lei Zhang, Maribel Acosta, Michael Färber, Steffen Thoma and Achim Rettinger. "BreXearch: Exploring Brexit Data Using Cross-Lingual and Cross-Media Semantic Search". In: Proceedings of the ISWC 2017 Posters & Demonstrations Track within the 16th International Semantic Web Conference (ISWC 2017). Vienna, Austria, 2017.

{"references": ["Lei Zhang, Maribel Acosta, Michael F\u00e4rber, Steffen Thoma and Achim Rettinger. \"BreXearch: Exploring Brexit Data Using Cross-Lingual and Cross-Media Semantic Search\". In: Proceedings of the ISWC 2017 Posters & Demonstrations Track within the 16th International Semantic Web Conference (ISWC 2017). Vienna, Austria, 2017."]}

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Keywords

social media, semantic search, information extraction, media content, Brexit, news articles, TV, semantic annotation

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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