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| − | ==Fake news Challenge==
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| − | http://www.fakenewschallenge.org/
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| − | Exploring how artificial intelligence technologies could be leveraged to combat fake news.
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| − | ===Stance Detection dataset for FNC1===
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| − | https://github.com/FakeNewsChallenge/fnc-1
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| − | ===Winner team===
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| − | ====First place - Team SOLAT in the SWEN====
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| − | https://github.com/Cisco-Talos/fnc-1
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| − | The data provided is (headline, body, stance) instances, where stance is one of {unrelated, discuss, agree, disagree}. The dataset is provided as two CSVs:
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| − | * '''train_bodies.csv''' : This file contains the body text of articles (the articleBody column) with corresponding IDs (Body ID)
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| − | * '''train_stances.csv''' : This file contains the labeled stances (the Stance column) for pairs of article headlines (Headline) and article bodies (Body ID, referring to entries in train_bodies.csv).
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| − | The distribution of Stance classes in train_stances.csv is as follows:
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| − | rows unrelated discuss agree disagree
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| − | 49972 0.73131 0.17828 0.0736012 0.0168094
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