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| + | ==Fake news Challenge== | ||
| + | http://www.fakenewschallenge.org/ | ||
| + | Exploring how artificial intelligence technologies could be leveraged to combat fake news. | ||
| + | |||
| + | |||
| + | ===Stance Detection dataset for FNC1=== | ||
| + | https://github.com/FakeNewsChallenge/fnc-1 | ||
| + | |||
| + | ===Winner team=== | ||
| + | |||
| + | ====First place - Team SOLAT in the SWEN==== | ||
| + | https://github.com/Cisco-Talos/fnc-1 | ||
| + | |||
| + | The data provided is (headline, body, stance) instances, where stance is one of {unrelated, discuss, agree, disagree}. The dataset is provided as two CSVs: | ||
| + | |||
| + | * '''train_bodies.csv''' : This file contains the body text of articles (the articleBody column) with corresponding IDs (Body ID) | ||
| + | |||
| + | * '''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). | ||
| + | |||
| + | |||
| + | The distribution of Stance classes in train_stances.csv is as follows: | ||
| + | |||
| + | rows unrelated discuss agree disagree | ||
| + | 49972 0.73131 0.17828 0.0736012 0.0168094 | ||
Revision as of 19:54, 3 April 2019
Contents
Fake news Challenge
http://www.fakenewschallenge.org/
Exploring how artificial intelligence technologies could be leveraged to combat fake news.
Stance Detection dataset for FNC1
https://github.com/FakeNewsChallenge/fnc-1
Winner team
First place - Team SOLAT in the SWEN
https://github.com/Cisco-Talos/fnc-1
The data provided is (headline, body, stance) instances, where stance is one of {unrelated, discuss, agree, disagree}. The dataset is provided as two CSVs:
- train_bodies.csv : This file contains the body text of articles (the articleBody column) with corresponding IDs (Body ID)
- 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).
The distribution of Stance classes in train_stances.csv is as follows:
rows unrelated discuss agree disagree 49972 0.73131 0.17828 0.0736012 0.0168094
