Search Results for author: Fatma Arslan

Found 5 papers, 1 papers with code

A Dashboard for Mitigating the COVID-19 Misinfodemic

no code implementations EACL 2021 Zhengyuan Zhu, Kevin Meng, Josue Caraballo, Israa Jaradat, Xiao Shi, Zeyu Zhang, Farahnaz Akrami, Haojin Liao, Fatma Arslan, Damian Jimenez, Mohanmmed Samiul Saeef, Paras Pathak, Chengkai Li

This paper describes the current milestones achieved in our ongoing project that aims to understand the surveillance of, impact of and intervention on COVID-19 misinfodemic on Twitter.


Modeling Factual Claims with Semantic Frames

no code implementations LREC 2020 Fatma Arslan, Josue Caraballo, Damian Jimenez, Chengkai Li

In this paper, we introduce an extension of the Berkeley FrameNet for the structured and semantic modeling of factual claims.

Fact Checking

A Benchmark Dataset of Check-worthy Factual Claims

no code implementations29 Apr 2020 Fatma Arslan, Naeemul Hassan, Chengkai Li, Mark Tremayne

In this paper we present the ClaimBuster dataset of 23, 533 statements extracted from all U. S. general election presidential debates and annotated by human coders.

Fact Checking

Gradient-Based Adversarial Training on Transformer Networks for Detecting Check-Worthy Factual Claims

1 code implementation18 Feb 2020 Kevin Meng, Damian Jimenez, Fatma Arslan, Jacob Daniel Devasier, Daniel Obembe, Chengkai Li

We present a study on the efficacy of adversarial training on transformer neural network models, with respect to the task of detecting check-worthy claims.

text-classification Text Classification

ClaimPortal: Integrated Monitoring, Searching, Checking, and Analytics of Factual Claims on Twitter

no code implementations ACL 2019 Sarthak Majithia, Fatma Arslan, Sumeet Lubal, Damian Jimenez, Priyank Arora, Josue Caraballo, Chengkai Li

We present ClaimPortal, a web-based platform for monitoring, searching, checking, and analyzing English factual claims on Twitter from the American political domain.

Fact Checking

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