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The outbreak of COVID-19 highlights the need for a more harmonized, less privacy-concerning, easily accessible approach to monitoring the human mobility that has been proved to be associated with the viral transmission. In this study, we…

Natural disasters, such as floods, tornadoes, or wildfires, are increasingly pervasive as the Earth undergoes global warming. It is difficult to predict when and where an incident will occur, so timely emergency response is critical to…

One of the most significant issues as attended a lot in recent years is that of recognizing the sentiments and emotions in social media texts. The analysis of sentiments and emotions is intended to recognize the conceptual information such…

Compared with traditional news media, social media nowadays provides a richer and more timely source of news. We are interested in multi-spatial level event detection from geo-tagged tweet streams. Specifically, in this paper we (1) examine…

Personality types are important in various fields as they hold relevant information about the characteristics of a human being in an explainable format. They are often good predictors of a person's behaviors in a particular environment and…

With the emergence of the COVID-19 pandemic, the political and the medical aspects of disinformation merged as the problem got elevated to a whole new level to become the first global infodemic. Fighting this infodemic has been declared one…

This paper proposes a topic modeling method that scales linearly to billions of documents. We make three core contributions: i) we present a topic modeling method, Tensor Latent Dirichlet Allocation (TLDA), that has identifiable and…

Sentiment analysis on social media such as Twitter provides organizations and individuals an effective way to monitor public emotions towards them and their competitors. As a result, sentiment analysis has become an important and…

In this paper, we present an updated version of the NELA-GT-2018 dataset (N{\o}rregaard, Horne, and Adal{\i} 2019), entitled NELA-GT-2019. NELA-GT-2019 contains 1.12M news articles from 260 sources collected between January 1st 2019 and…

Existing rumor detection strategies typically provide detection labels while ignoring their explanation. Nonetheless, providing pieces of evidence to explain why a suspicious tweet is rumor is essential. As such, a novel model, LOSIRD, was…

News articles covering policy issues are an essential source of information in the social sciences and are also frequently used for other use cases, e.g., to train NLP language models. To derive meaningful insights from the analysis of…

Social media has increasingly played a key role in emergency response: first responders can use public posts to better react to ongoing crisis events and deploy the necessary resources where they are most needed. Timeline extraction and…

Well-annotated data is a prerequisite for good Natural Language Processing models. Too often, though, annotation decisions are governed by optimizing time or annotator agreement. We make a case for nuanced efforts in an interdisciplinary…

Large Language Models (LLMs) are increasingly deployed as active participants on public social media platforms, yet their behavior in these unconstrained social environments remains largely unstudied. Existing datasets, drawn primarily from…

Event detection using social media streams needs a set of informative features with strong signals that need minimal preprocessing and are highly associated with events of interest. Identifying these informative features as keywords from…

Recently, powerful Large Language Models (LLMs) have become easily accessible to hundreds of millions of users world-wide. However, their strong capabilities and vast world knowledge do not come without associated privacy risks. In this…

Social media plays a significant role in disaster management by providing valuable data about affected people, donations and help requests. Recent studies highlight the need to filter information on social media into fine-grained content…

The right to protest is perceived as one of the primary civil rights. Citizens participate in mass demonstrations to express themselves and exercise their democratic rights. However, because of the large number of participants, protests may…

The rise of online aggression on social media is evolving into a major point of concern. Several machine and deep learning approaches have been proposed recently for detecting various types of aggressive behavior. However, social media are…

Social media data has become a vital resource for studying mental health, offering real-time insights into thoughts, emotions, and behaviors that traditional methods often miss. Progress in this area has been facilitated by benchmark…