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The proliferation of hate speech on social media is one of the serious issues that is bringing huge impacts to society: an escalation of violence, discrimination, and social fragmentation. The problem of detecting hate speech is…

Topic modelling with innovative deep learning methods has gained interest for a wide range of applications that includes COVID-19. Topic modelling can provide, psychological, social and cultural insights for understanding human behaviour in…

Social media was one of the most popular forms of communication among young people with digital access during the pandemic. Consequently, crucial debates and discussions about the pandemic crisis have also developed on social media…

The advent of the COVID-19 pandemic has undoubtedly affected the political scene worldwide and the introduction of new terminology and public opinions regarding the virus has further polarized partisan stances. Using a collection of tweets…

The massive spread of false information on social media has become a global risk especially in a global pandemic situation like COVID-19. False information detection has thus become a surging research topic in recent months. NLP4IF-2021…

Social media is recognized as an important source for deriving insights into public opinion dynamics and social impacts due to the vast textual data generated daily and the 'unconstrained' behavior of people interacting on these platforms.…

Measuring public attitudes toward wildlife provides crucial insights into our relationship with nature and helps monitor progress toward Global Biodiversity Framework targets. Yet, conducting such assessments at a global scale is…

The COVID-19 pandemic is having a serious adverse impact on the lives of people across the world. COVID-19 has exacerbated community-wide depression, and has led to increased drug abuse brought about by isolation of individuals as a result…

Transcending the binary categorization of racist and xenophobic texts, this research takes cues from social science theories to develop a four dimensional category for racism and xenophobia detection, namely stigmatization, offensiveness,…

Online Social Networks serve as fertile ground for harmful behavior, ranging from hate speech to the dissemination of disinformation. Malicious actors now have unprecedented freedom to misbehave, leading to severe societal unrest and dire…

Social media has become an important tool to share information about crisis events such as natural disasters and mass attacks. Detecting actionable posts that contain useful information requires rapid analysis of huge volume of data in…

The rapid increase in hate speech on social media has exposed an unprecedented impact on society, making automated methods for detecting such content important. Unlike prior black-box models, we propose a novel transparent method for…

In this paper, we collect and study Twitter communications to understand the socio-economic impact of COVID-19 in the United States during the early days of the pandemic. Our analysis reveals that COVID-19 gripped the nation during this…

Large Language Models (LLMs) can generate fluent political text at scale, raising concerns about synthetic discourse during crises and social conflict. Existing AI-text detection often focuses on sentence-level cues such as perplexity,…

Currently, the world is in the midst of a severe global pandemic, which has affected all aspects of people's lives. As a result, there is a deluge of COVID-related digital media articles published in the United States, due to the disparate…

COVID-19 pandemic has sharply projected the globally persistent multi-dimensional fundamental challenges in securing general socio-economic wellbeing of the society. The problems intensify with increasing population densities and also vary…

This paper presents our work for the Violence Inciting Text Detection shared task in the First Workshop on Bangla Language Processing. Social media has accelerated the propagation of hate and violence-inciting speech in society. It is…

Information from social media can provide essential information for emergency response during natural disasters in near real-time. However, it is difficult to identify the disaster-related posts among the large amounts of unstructured data…

Social media is a great source of data for users reporting information and regarding their health and how various things have had an effect on them. This paper presents various approaches using Transformers and Large Language Models and…

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…