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ZENODO
Dataset . 2018
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Webis Wikipedia Text Reuse Corpus 2018 (Webis-Wikipedia-Text-Reuse-18)

Authors: Milad Alshomary; Michael Völske; Henning Wachsmuth; Benno Stein; Matthias Hagen; Martin Potthast;

Webis Wikipedia Text Reuse Corpus 2018 (Webis-Wikipedia-Text-Reuse-18)

Abstract

The Wikipedia Text Reuse Corpus 2018 (Webis-Wikipedia-Text-Reuse-18) containing text reuse cases extracted from within Wikipedia and in between Wikipedia and a sample of the Common Crawl. The corpus has following structure: wikipedia.jsonl.bz2: Each line, representing a Wikipedia article, contains a json array of article_id, article_title, and article_body within-wikipedia-tr-01.jsonl.bz2: Each line, representing a text reuse case, contains a json array of s_id (source article id), t_id (target article id), s_text (source text), t_text (target text) within-wikipedia-tr-02.jsonl.bz2: Each line, representing a text reuse case, contains a json array of s_id (source article id), t_id (target article id), s_text (source text), t_text (target text) preprocessed-web-sample.jsonl.xz: Each line, representing a web page, contains a json object of d_id, d_url, and content without-wikipedia-tr.jsonl.bz2: Each line, representing a text reuse case, contains a json array of s_id (Wikipedia article id), d_id (web page id), s_text (article text), d_content (web page content) The datasets were extracted in the work by Alshomary et al. 2018 that aimed to study the text reuse phenomena related to Wikipedia at scale. A pipeline for large scale text reuse extraction was developed and used on Wikipedia and the CommonCrawl.

{"references": ["Milad Alshomary, Michael V\u00f6lske, Tristan Licht, Henning Wachsmuth, Benno Stein, Matthias Hagen, and Martin Potthast. Wikipedia Text Reuse: Within and Without. In Leif Azzopardi et al, editors, Advances in Information Retrieval. 41st European Conference on IR Research (ECIR 2019) volume 11437 of Lecture Notes in Computer Science, pages 747-754, Berlin Heidelberg New York, April 2019. Springer."]}

Keywords

wikipedia, common crawl, text reuse

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  • citations
    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.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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visibility
download
citations
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).
BIP!Citations provided by BIP!
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!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
0
Average
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313
205