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Stance Detection

13 papers with code · Natural Language Processing

Stance detection is the extraction of a subject's reaction to a claim made by a primary actor. It is a core part of a set of approaches to fake news assessment.

Example:

  • Source: "Apples are the most delicious fruit in existence"
  • Reply: "Obviously not, because that is a reuben from Katz's"
  • Stance: deny

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Greatest papers with code

A simple but tough-to-beat baseline for the Fake News Challenge stance detection task

11 Jul 2017uclmr/fakenewschallenge

Identifying public misinformation is a complicated and challenging task.

STANCE DETECTION

Stance Detection with Bidirectional Conditional Encoding

EMNLP 2016 sheffieldnlp/stance-conditional

Stance detection is the task of classifying the attitude expressed in a text towards a target such as Hillary Clinton to be "positive", negative" or "neutral".

STANCE DETECTION

A Retrospective Analysis of the Fake News Challenge Stance Detection Task

13 Jun 2018hanselowski/athene_system

To date, there is no in-depth analysis paper to critically discuss FNC-1's experimental setup, reproduce the results, and draw conclusions for next-generation stance classification methods.

STANCE DETECTION

Detecting Incongruity Between News Headline and Body Text via a Deep Hierarchical Encoder

17 Nov 2018david-yoon/detecting-incongruity

Some news headlines mislead readers with overrated or false information, and identifying them in advance will better assist readers in choosing proper news stories to consume.

DATA AUGMENTATION FAKE NEWS DETECTION INCONGRUITY DETECTION STANCE DETECTION

A Retrospective Analysis of the Fake News Challenge Stance-Detection Task

COLING 2018 UKPLab/coling2018_fake-news-challenge

To date, there is no in-depth analysis paper to critically discuss FNC-1{'}s experimental setup, reproduce the results, and draw conclusions for next-generation stance classification methods.

STANCE DETECTION

A Tweet Dataset Annotated for Named Entity Recognition and Stance Detection

15 Jan 2019dkucuk/Tweet-Dataset-NER-SD

Annotated datasets in different domains are critical for many supervised learning-based solutions to related problems and for the evaluation of the proposed solutions.

NAMED ENTITY RECOGNITION STANCE DETECTION

Combining Similarity Features and Deep Representation Learning for Stance Detection in the Context of Checking Fake News

2 Nov 2018LuisPB7/fnc-msc

Specifically, we use bi-directional Recurrent Neural Networks, together with max-pooling over the temporal/sequential dimension and neural attention, for representing (i) the headline, (ii) the first two sentences of the news article, and (iii) the entire news article.

DOCUMENT CLASSIFICATION NATURAL LANGUAGE INFERENCE REPRESENTATION LEARNING STANCE DETECTION

Stance Prediction for Russian: Data and Analysis

5 Sep 2018npenzin/rustance

As well as presenting this openly-available dataset, the first of its kind for Russian, the paper presents a baseline for stance prediction in the language.

STANCE DETECTION

A Richly Annotated Corpus for Different Tasks in Automated Fact-Checking

CONLL 2019 UKPLab/conll2019-snopes-crawling

Automated fact-checking based on machine learning is a promising approach to identify false information distributed on the web.

STANCE DETECTION

Incorporating Label Dependencies in Multilabel Stance Detection

IJCNLP 2019 willferreira/multilabel-stance-detection

We propose a method that explicitly incorporates label dependencies in the training objective and compare it against a variety of baselines, as well as a reduction of multilabel to multiclass learning.

STANCE DETECTION