Related papers: Fighting the COVID-19 Infodemic with a Holistic BE…

Sentiment analysis is a process widely used in opinion mining campaigns conducted today. This phenomenon presents applications in a variety of fields, especially in collecting information related to the attitude or satisfaction of users…

This paper presents the HYBRINFOX method used to solve Task 2 of Subjectivity detection of the CLEF 2024 CheckThat! competition. The specificity of the method is to use a hybrid system, combining a RoBERTa model, fine-tuned for subjectivity…

In this paper, we present our participation in SemEval-2020 Task-12 Subtask-A (English Language) which focuses on offensive language identification from noisy labels. To this end, we developed a hybrid system with the BERT classifier…

While the COVID-19 pandemic continues its global devastation, numerous accompanying challenges emerge. One important challenge we face is to efficiently and effectively use recently gathered data and find computational tools to combat the…

The paper describes a system developed for Task 1 at SMM4H 2023. The goal of the task is to automatically distinguish tweets that self-report a COVID-19 diagnosis (for example, a positive test, clinical diagnosis, or hospitalization) from…

There is a growing interest in understanding how humans initiate and hold conversations. The affective understanding of conversations focuses on the problem of how speakers use emotions to react to a situation and to each other. In the…

In this paper, we report our method for the Information Extraction task in 2019 Language and Intelligence Challenge. We incorporate BERT into the multi-head selection framework for joint entity-relation extraction. This model extends…

The sudden widespread menace created by the present global pandemic COVID-19 has had an unprecedented effect on our lives. Man-kind is going through humongous fear and dependence on social media like never before. Fear inevitably leads to…

Identification of Fake News plays a prominent role in the ongoing pandemic, impacting multiple aspects of day-to-day life. In this work we present a solution to the shared task titled COVID19 Fake News Detection in English, scoring the 50th…

The spread of misinformation in social media outlets has become a prevalent societal problem and is the cause of many kinds of social unrest. Curtailing its prevalence is of great importance and machine learning has shown significant…

COVID-19, has led to a global pandemic that strained the healthcare systems. Early and accurate detection is crucial for controlling the spread of the virus. While reverse transcription polymerase chain reaction test is the gold standard…

COVID-19 has created a pandemic around the world, paused the path of building the future, and still ongoing without having any long-term solution shortly. The time taken in vaccine distribution is too slow compared to the spread of…

The novel corona-virus disease (also known as COVID-19) has led to a pandemic, impacting more than 200 countries across the globe. With its global impact, COVID-19 has become a major concern of people almost everywhere, and therefore there…

For the last two years, from 2020 to 2021, COVID-19 has broken disease prevention measures in many countries, including Vietnam, and negatively impacted various aspects of human life and the social community. Besides, the misleading…

We describe our system for WNUT-2020 shared task on the identification of informative COVID-19 English tweets. Our system is an ensemble of various machine learning methods, leveraging both traditional feature-based classifiers as well as…

An infodemic refers to an enormous amount of true information and misinformation disseminated during a disease outbreak. Detecting misinformation at the early stage of an infodemic is key to reduce its harm to public health. An early stage…

This paper gives the overview of the first shared task at FIRE 2020 on fake news detection in the Urdu language. This is a binary classification task in which the goal is to identify fake news using a dataset composed of 900 annotated news…

The evolution of social media platforms have empowered everyone to access information easily. Social media users can easily share information with the rest of the world. This may sometimes encourage spread of fake news, which can result in…

During the outbreak of COVID-19 pandemic, several research areas joined efforts to mitigate the damages caused by SARS-CoV-2. In this paper we present an interpretability analysis of a convolutional neural network based model for COVID-19…

In recent years, social media has enabled users to get exposed to a myriad of misinformation and disinformation; thus, misinformation has attracted a great deal of attention in research fields and as a social issue. To address the problem,…