Related papers: NutCracker at WNUT-2020 Task 2: Robustly Identifyi…
Along with the Coronavirus pandemic, another crisis has manifested itself in the form of mass fear and panic phenomena, fueled by incomplete and often inaccurate information. There is therefore a tremendous need to address and better…
We propose a simple and general method to regularize the fine-tuning of Transformer-based encoders for text classification tasks. Specifically, during fine-tuning we generate adversarial examples by perturbing the word embeddings of the…
The COVID-19 pandemic led to an infodemic where an overwhelming amount of COVID-19 related content was being disseminated at high velocity through social media. This made it challenging for citizens to differentiate between accurate and…
We describe Bioformer team's participation in the multi-label topic classification task for COVID-19 literature (track 5 of BioCreative VII). Topic classification is performed using different BERT models (BioBERT, PubMedBERT, and…
The current COVID-19 pandemic overloads healthcare systems, including radiology departments. Though several deep learning approaches were developed to assist in CT analysis, nobody considered study triage directly as a computer science…
The rapid growth of social media content during the current pandemic provides useful tools for disseminating information which has also become a root for misinformation. Therefore, there is an urgent need for fact-checking and effective…
Vaccination is important to minimize the risk and spread of various diseases. In recent years, vaccination has been a key step in countering the COVID-19 pandemic. However, many people are skeptical about the use of vaccines for various…
SemEval-2019 Task 6 (Zampieri et al., 2019b) requires us to identify and categorise offensive language in social media. In this paper we will describe the process we took to tackle this challenge. Our process is heavily inspired by Sosa…
In our paper, we present Deep Learning models with a layer differentiated training method which were used for the SHARED TASK@ CONSTRAINT 2021 sub-tasks COVID19 Fake News Detection in English and Hostile Post Detection in Hindi. We propose…
In this paper, we describe our system submitted for SemEval 2020 Task 9, Sentiment Analysis for Code-Mixed Social Media Text alongside other experiments. Our best performing system is a Transfer Learning-based model that fine-tunes…
The paper is devoted to the participation of the TUDublin team in Constraint@AAAI2021 - COVID19 Fake News Detection Challenge. Today, the problem of fake news detection is more acute than ever in connection with the pandemic. The number of…
The rapid outbreak of COVID-19 has caused humanity to come to a stand-still and brought with it a plethora of other problems. COVID-19 is the first pandemic in history when humanity is the most technologically advanced and relies heavily on…
This paper describes a pilot NER system for Twitter, comprising the USFD system entry to the W-NUT 2015 NER shared task. The goal is to correctly label entities in a tweet dataset, using an inventory of ten types. We employ structured…
To curb the problem of false information, social media platforms like Twitter started adding warning labels to content discussing debunked narratives, with the goal of providing more context to their audiences. Unfortunately, these labels…
This paper describes our system submitted to SemEval 2019 Task 7: RumourEval 2019: Determining Rumour Veracity and Support for Rumours, Subtask A (Gorrell et al., 2019). The challenge focused on classifying whether posts from Twitter and…
Detecting humor is a challenging task since words might share multiple valences and, depending on the context, the same words can be even used in offensive expressions. Neural network architectures based on Transformer obtain…
This paper makes two key contributions. First, it argues that highly specialized rare content classifiers trained on small data typically have limited exposure to the richness and topical diversity of the negative class (dubbed anticontent)…
The increment of toxic comments on online space is causing tremendous effects on other vulnerable users. For this reason, considerable efforts are made to deal with this, and SemEval-2021 Task 5: Toxic Spans Detection is one of those. This…
The purpose of this case study is to leverage the concepts and tools presented in the preceding chapters and apply them in a real world social cybersecurity context. With the COVID-19 pandemic emerging as a defining event of the 21st…
The way people respond to messaging from public health organizations on social media can provide insight into public perceptions on critical health issues, especially during a global crisis such as COVID-19. It could be valuable for…