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On Classifying whether Two Texts are on the Same Side of an Argument ...
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AWESSOME : An unsupervised sentiment intensity scoring framework using neural word embeddings
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Evaluating multilingual text encoders for unsupervised cross-lingual retrieval
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Webis Argument Quality Corpus 2020 (Webis-ArgQuality-20) ...
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Webis Argument Quality Corpus 2020 (Webis-ArgQuality-20) ...
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Overview of PAN 2020: Authorship Verification, Celebrity Profiling, Profiling Fake News Spreaders on Twitter, and Style Change Detection
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Overview of PAN 2019: Bots and Gender Profiling, Celebrity Profiling, Cross-domain Authorship Attribution and Style Change Detection
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BuzzFeed-Webis Fake News Corpus 2016 ...
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Abstract:
The corpus comprises the output of 9 publishers in a week close to the US elections. Among the selected publishers are 6 prolific hyperpartisan ones (three left-wing and three right-wing), and three mainstream publishers (see Table 1). All publishers earned Facebook’s blue checkmark, indicating authenticity and an elevated status within the network. For seven weekdays (September 19 to 23 and September 26 and 27), every post and linked news article of the 9 publishers was fact-checked by professional journalists at BuzzFeed. In total, 1,627 articles were checked, 826 mainstream, 256 left-wing and 545 right-wing. The imbalance between categories results from differing publication frequencies. ... : {"references": ["Martin Potthast, Johannes Kiesel, Kevin Reinartz, Janek Bevendorff, and Benno Stein. A Stylometric Inquiry into Hyperpartisan and Fake News. In 56th Annual Meeting of the Association for Computational Linguistics (ACL 2018), pages 231-240, July 2018. Association for Computational Linguistics."]} ...
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Keyword:
Fake News; Hyperpartisan News; News; News articles
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URL: https://dx.doi.org/10.5281/zenodo.1239675 https://zenodo.org/record/1239675
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Overview of PAN 2018. Author identification, author profiling, and author obfuscation
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CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies
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Overview of PAN'17: Author Identification, Author Profiling, and Author Obfuscation
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