MuMiN: A Large-Scale Multilingual Multimodal Fact-Checked Misinformation Social Network Dataset

02/23/2022
by   Dan Saattrup Nielsen, et al.
17

Misinformation is becoming increasingly prevalent on social media and in news articles. It has become so widespread that we require algorithmic assistance utilising machine learning to detect such content. Training these machine learning models require datasets of sufficient scale, diversity and quality. However, datasets in the field of automatic misinformation detection are predominantly monolingual, include a limited amount of modalities and are not of sufficient scale and quality. Addressing this, we develop a data collection and linking system (MuMiN-trawl), to build a public misinformation graph dataset (MuMiN), containing rich social media data (tweets, replies, users, images, articles, hashtags) spanning 21 million tweets belonging to 26 thousand Twitter threads, each of which have been semantically linked to 13 thousand fact-checked claims across dozens of topics, events and domains, in 41 different languages, spanning more than a decade. The dataset is made available as a heterogeneous graph via a Python package (mumin). We provide baseline results for two node classification tasks related to the veracity of a claim involving social media, and demonstrate that these are challenging tasks, with the highest macro-average F1-score being 62.55 respectively. The MuMiN ecosystem is available at https://mumin-dataset.github.io/, including the data, documentation, tutorials and leaderboards.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/07/2021

HumAID: Human-Annotated Disaster Incidents Data from Twitter with Deep Learning Benchmarks

Social networks are widely used for information consumption and dissemin...
research
02/14/2022

Matching Tweets With Applicable Fact-Checks Across Languages

An important challenge for news fact-checking is the effective dissemina...
research
04/23/2021

Claim Detection in Biomedical Twitter Posts

Social media contains unfiltered and unique information, which is potent...
research
05/04/2022

MM-Claims: A Dataset for Multimodal Claim Detection in Social Media

In recent years, the problem of misinformation on the web has become wid...
research
04/14/2020

Standardizing and Benchmarking Crisis-related Social Media Datasets for Humanitarian Information Processing

Time-critical analysis of social media streams is important for humanita...
research
12/09/2021

Detecting Potentially Harmful and Protective Suicide-related Content on Twitter: A Machine Learning Approach

Research shows that exposure to suicide-related news media content is as...
research
10/24/2016

Learning Reporting Dynamics during Breaking News for Rumour Detection in Social Media

Breaking news leads to situations of fast-paced reporting in social medi...

Please sign up or login with your details

Forgot password? Click here to reset