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Fake News Detection

31 평가 기록 10 datasets

Fake News Detection is a natural language processing task that involves identifying and classifying news articles or other types of text as real or fake. The goal of fake news detection is to develop algorithms that can automatically identify and flag fake news articles, which can be used to combat misinformation and promote the dissemination of accurate information.

개요는 각 항목의 일부입니다. 위 탭에서 전체 기록을 페이지별로 탐색할 수 있습니다.

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Papers with Code 아카이브의 데이터셋별 기록 예시입니다. 평가 조건과 지표 방향이 검증되지 않아 순위를 의미하지 않습니다.

Dataset기록된 모델 예시MetricPaperCode
Sepúlveda-Torres R., Vicente M., Saquete E., Lloret E., Palomar M. (2021)
Weighted Accuracy: 90.73Per-class Accuracy (Agree): 75.03Per-class Accuracy (Disagree): 63.41Per-class Accuracy (Discuss): 85.97
논문 코드
Persuasive Writing Strategy
F1: 55.8
논문 코드
Text-Transformers + Five-fold five model cross-validation +Pseudo Label Algorithm
Unpaired Accuracy: 98.5%
논문 코드
Hybrid CNNs (Text + All)
Validation Accuracy: 0.247Test Accuracy: 0.274
논문 코드
Ensemble Model + Heuristic Post-Processing
F1: 0.9883
논문 코드
Auxiliary IndicBert
F1 score: 0.7741
논문 코드
SEMI-FND
Accuracy: 85.80%
논문 -
Convolutional Tsetlin Machine
1:1 Accuracy: 91.21
논문 -
TextRNN
Accuracy: 92.4
논문 코드
SEMI-FND
Accuracy: 86.83%
논문 -

데이터셋

10개
FNC-1RAWFCGrover-MegaLIARCOVID-19 Fake News DatasetHostility Detection Dataset in HindiMediaEval2016PolitiFactSocial mediaWeibo NER

논문

라이브러리

Papers with Code 리더보드 row에 연결된 구현 저장소입니다.

github.com/jadecurl/hiss 1 논문
github.com/bedarkarpriyanka/NLP-Project-Fake-News-Detection 1 논문
github.com/ekagra-ranjan/fake-news-detection-LIAR-pytorch 1 논문
github.com/ExploringLies/lies-have-short-legs 1 논문
github.com/JelenaBanjac/AppliedDataAnalysis 1 논문
github.com/JelenaBanjac/lies-have-short-legs 1 논문
github.com/kiranrawat/Detecting-Fake-News-On-Social-Media 1 논문
github.com/manideep2510/siamese-BERT-fake-news-detection-LIAR 1 논문