Kathleen M Carley

Carnegie Mellon University | CMU · Software and Societal Systems

Psychological inoculation is a promising and potentially scalable approach to counter misinformation. The goal of inoculation is to teach people to recognize manipulation techniques, such as emotional language, commonly found in misinformation online. While there is substantial evidence that inoculation increases technique recognition when directly...

Inauthentic local news organizations, otherwise known as pink slime, have become a serious problem exploiting the trust of local news since their creation ahead of the 2020 U.S. Presidential election. In this paper, we apply the BEND framework, a methodology of classifying social media posts as belonging to sixteen network and narrative maneuvers,...

Objective This study analyzes gender disparities between men and women otolaryngology faculty in the top 20 otolaryngology departments ranked by research output and discusses the implications of these disparities. Methods This was a cross‐sectional study of all articles published by faculty from January 2020 to December 2021 at the top 20 otolaryn...

Much research has focused on the role of the alt-right in pushing far-right narratives into mainstream discourse. In this work, we focus on the alt-right’s effects on extremist narratives themselves. From 2012 to 2017, we find a rise in alt-right, 4chan-like discourse styles across multiple communication platforms known for white supremacist extrem...

Pink slime news sites are politically polarized Web sites controlled by partisan national organizations that masquerade as local news. Instead of authentic community reporting, these sites rely on automated algorithms and APIs to fill in news articles between their politically charged messaging aimed at influencing votes. Over 1,000 of these sites...

The dissemination of disinformation has become a formidable weapon, with nation-states exploiting social media platforms to engineer narratives favorable to their geopolitical interests. This study delved into Russia’s orchestrated disinformation campaign, in three times periods of the 2022 Russian-Ukraine War: its incursion, its midpoint and the U...

Automated political campaigns in the digital space can influence electoral votes and tilt the balance of power. We developed a compact ensemble approach named Tiny BotBuster to identify automated bot users, then we applied the Combined Synchronization Index to reveal the political actors working together. We applied our techniques to the 2024 Indon...

Effective public health messaging benefits from understanding antecedents to unstable attitudes that are more likely to be influenced. This work investigates the relationship between moral and emotional bases for attitudes towards COVID-19 vaccines and variance in stance. Evaluating nearly 1 million X users over a two month period, we find that emo...

Social media platforms are highly interconnected because many users maintain a presence across multiple platforms. Consequently, efforts to limit the spread of misinformation taken by individual platforms can have complex consequences on misinformation diffusion across the social media ecosystem. This is further complicated by the diverse social st...

In an attempt to mimic the complex paths through which unreliable content spreads between search engines and social media, we explore the impact of incorporating both webgraph and large-scale social media contexts into website credibility classification and discovery systems. We further explore the usage of what we define as \textit{dredge words} o...

This paper examines Russia's propaganda discourse on Twitter during the 2022 invasion of Ukraine. The study employs network analysis, natural language processing (NLP) techniques, and qualitative analysis to identify key communities and narratives associated with the prevalent and damaging narrative of "fascism/Nazism" in discussions related to the...

During the COVID-19 pandemic, the proliferation of misinformation on social media has been rapidly increasing. Automated Bot authors are believed to be significant contributors of this surge. It is hypothesized that Bot authors deliberately craft online misinformation aimed at triggering and exploiting human cognitive biases, thereby enhancing twee...

This study analyzes two covert Chinese bot networks, employing tweet-based and account-based methods to find detection evasion tactics. We reveal the use of message artifacts that disguise spam, engagement strategies that mimic human interaction, and behavioral patterns suggesting algorithmic control. We uncover bot maintenance practices and algori...

Bots are automated social media users that can be used to amplify (mis)information and sow harmful discourse. In order to effectively influence users, bots can be generated to reproduce human user behavior. Indeed, people tend to trust information coming from users with profiles that fit roles they expect to exist, such as users with gender role st...

The proliferation of unreliable news domains on the internet has had wide-reaching negative impacts on society. We introduce and evaluate interventions aimed at reducing traffic to unreliable news domains from search engines while maintaining traffic to reliable domains. We build these interventions on the principles of fairness (penalize sites for...

To influence the information landscape preceding and during the military invasion of Ukraine in February 2022, Russia initiated a disinformation campaign portraying Ukraine as a Nazi state. This study aims to compare discussions related to this campaign on Twitter and Telegram. The analysis reveals that the Nazis and Ukraine narrative was constant...

This paper explores the complexities of Russian anti-war discussions on Twitter following the invasion of Ukraine in 2022. Our research seeks to uncover the fundamental dynamics of this discourse within the Russian-speaking Twitter community, illuminating influential figures and interconnected communities, while closely examining the prevalence of...

Website reliability labels underpin almost all research in misinformation detection. However, misinformation sources often exhibit transient behavior, which makes many such labeled lists obsolete over time. We demonstrate that Search Engine Optimization (SEO) attributes provide strong signals for predicting news site reliability. We introduce a nov...

To influence the information landscape preceding and during the military invasion of Ukraine in February 2022, Russia initiated a disinformation campaign portraying Ukraine as a Nazi state. This study aims to compare discussions related to this campaign on Twitter and Telegram. The analysis reveals that the Nazis and Ukraine narrative was constant...

News journalism has evolved from traditional print media to social media, with a large proportion of readers consuming their news via digital means. Through an analysis of over 1.3 million posts across three social media platforms (Facebook, Twitter, Reddit) pertaining to the 2022 U.S. Midterm Elections, this analysis examines the difference in sha...

The COVID-19 pandemic of 2021 led to a worldwide health crisis that was accompanied by an infodemic. A group of 12 social media personalities, dubbed the “Disinformation Dozen”, were identified as key in spreading disinformation regarding the COVID-19 virus, treatments, and vaccines. This study focuses on the spread of disinformation propagated by...

This paper describes the challenges posed by pattern-of-life variations when carrying out automated detection of abnormal events (change detection) in longitudinal (over-time) social network data sets using standard social network measures. In this paper we present a new scheme for substantially removing pattern-of-life variations from longitudinal...

The dissemination of disinformation has become a formidable weapon, with nation-states exploiting social media platforms to engineer narratives favorable to their geopolitical interests. This study delved into Russia's orchestrated disinformation campaign, in three times periods of the 2022 Russian-Ukraine War: its incursion, its midpoint and the U...

Bots have been in the spotlight for many social media studies, for they have been observed to be participating in the manipulation of information and opinions on social media. These studies analyzed the activity and influence of bots in a variety of contexts: elections, protests, health communication and so forth. Prior to this analyzes is the iden...

Social media platforms are a key ground of information consumption and dissemination. Key figures like politicians, celebrities, and activists have leveraged on its wide user base for strategic communication. Strategic communications, or StratCom, is the deliberate act of information creation and distribution. Its techniques are used by key figures...

Rising US polarization in recent years has negatively impacted many friend and family relationships. To determine the best moral strategies for facilitating cross-party communication, we create an agent-based simulation underpinned by Moral Foundations Theory to model small-group moral conversations where the majority of agents align with either li...

As digitalization increases, countries employ digital diplomacy, harnessing digital resources to project their desired image. Digital diplomacy also encompasses the interactivity of digital platforms, providing a trove of public opinion that diplomatic agents can collect. Social media bots actively participate in political events through influencin...

Machine Learning has become increasingly popular in developing Intrusion Detection Systems (IDS) for cybersecurity. However, the focus has mainly been on achieving high detection accuracy rather than evaluating the impact on cybersecurity resiliency. In this paper, we use agent-based simulation to investigate the impact of different IDS algorithms...

Polarization, ideological and psychological distancing between groups, can cause dire societal fragmentation. Of chief concern is the role of social media in enhancing polarization through mechanisms like facilitating selective exposure to information. Researchers using user-generated content to measure polarization typically focus on direct commun...

Studying the expression of vulnerability – the psychological state that arises in moments of uncertainty, risk, and emotional exposure – is key to understanding how individuals cope during time of crisis. In this study, we synthesize past theoretical and qualitative work on vulnerability and present a psycholinguistic dictionary featuring seven dif...

Governments around the world leverage social media to enact public diplomacy. In this article, we examine Chinese diplomatic communication on Twitter during two highly controversial events through a social cybersecurity lens: then-Speaker Pelosi’s visit to Taiwan in early August 2022 and Taiwanese President Tsai’s visit to the U.S. in early April 2...

Agent-based simulations have been used in modeling transportation systems to gain deeper understanding of travel behavior and transport mode choices. This study focuses on analyzing the factors that influence transportation mode decisions specifically in developing countries. As motorcycles are the preferred mode of transport in these economies, we...

The 2022 Russian invasion of Ukraine is a war being fought both on the physical battlefield and online. This paper studies Telegram activity in the first weeks of the invasion, applying social cybersecurity methods to characterize the information environment on a platform that is popular in both Ukraine and Russia. In a study of over 4 million Tele...

In this work, we analyze the circumstances under which social influence operations are likely to succeed. These circumstances include the selection of Confederate agents to execute intentional perturbations and the selection of Perturbation strategies. We use Agent-Based Modelling (ABM) as a simulation technique to observe the effect of intentional...

Many researchers focus on developing virtual testbeds to assess the magnitude of cyberattack damage and evaluate the effectiveness of cyber defense strategies in different cyber attack scenarios. These testbeds provide a controlled and cost-effective environment for simulating attacks and studying their impact on organizational security. One of the...

The first year of the COVID-19 pandemic coincided with significant social and political changes. This article presents an exploratory analysis of Twitter users’ self-representations in the context of COVID-19. While some identities remained stable throughout the year, others appear to have been influenced by external events such as the Black Lives...

The cross-strait relationship between China and Taiwan is marked by increasing hostility around potential reunification. We analyze an unattributed bot network and how repeater bots engaged in an influence campaign against Taiwan following US House Speaker Nancy Pelosi’s visit to Taiwan in 2022. We examine the message amplification tactics employed...

Conspiracy theories (CTs) have thrived during the COVID-19 pandemic and continue to spread on social media despite attempts at fact-checking. The isolation and fear associated with this pandemic likely contributed to the generation and spread of these theories. Another possible factor is the high rate of Twitter users linking to off-platform altern...

Introduction France has seen two key protests within the term of President Emmanuel Macron: one in 2020 against Islamophobia, and another in 2023 against the pension reform. During these protests, there is much chatter on online social media platforms like Twitter. Methods In this study, we aim to analyze the differences between the online chatter...

In this study, we examined online conversations on Twitter about a Chinese balloon spotted over U.S. airspace in January 2023. We investigated the conversations between U.S.-based, China-based and accounts from the rest of the world. We also studied the difference between bots and human accounts within these conversations. We found that U.S.-based...

Social media platforms are information battlegrounds where actors or communities compete to influence ideas and beliefs. These platforms can benefit government and health organizations by quickly disseminating pertinent information about the COVID-19 vaccine to a large population. However, at the same time, the social-cyberspace domain has made it...

Agent-based simulations have been used in modeling transportation systems for traffic management and passenger flows. In this work, we hope to shed light on the complex factors that influence transportation mode decisions within developing countries, using Colombia as a case study. We model an ecosystem of human agents that decide at each time step...

Agent-based simulations have been used in modeling transportation systems for traffic management and passenger flows. In this work, we hope to shed light on the complex factors that influence transportation mode decisions within developing countries, using Colombia as a case study. We model an ecosystem of human agents that decide at each time step...

Background Online infodemics have represented a major obstacle to the offline success of public health interventions during the COVID-19 pandemic. Offline contexts have likewise fueled public susceptibility to online infodemics. We combine a large-scale dataset of Twitter conversations about face masks with high-performance machine learning tools t...

Masks have remained an important mitigation strategy in the fight against COVID-19 due to their ability to prevent the transmission of respiratory droplets between individuals. In this work, we provide a comprehensive quantitative analysis of the impact of mask-wearing. To this end, we propose a novel agent-based model of viral spread on networks w...

In this work, we analyze the circumstances under which social influence operations are likely to succeed. These circumstances include the selection of Confederate agents to execute intentional perturbations and the selection of Perturbation strategies. We use Agent-Based Modelling (ABM) as a simulation technique to observe the effect of intentional...

The rapid increase in China’s outward digital presence on western social media platforms highlights China’s priorities for promoting pro-Chinese narratives and stories in recent years. Simultaneously, China has increasingly been accused of launching information operations using bot activity, puppet accounts, and other inauthentic activity to amplif...

Online communities of involuntary celibates (incels) are a prominent source of misogynist hate speech. In this paper, we use quantitative text and network analysis approaches to examine how identity groups are discussed on incels.is, the largest black-pilled incels forum. We find that this community produces a wide range of novel identity terms and...

We present a dataset and classifier for detecting the language of white supremacist extremism, a growing issue in online hate speech. Our weakly supervised classifier is trained on large datasets of text from explicitly white supremacist domains paired with neutral and anti-racist data from similar domains. We demonstrate that this approach improve...

Despite rapid development, current bot detection models still face challenges in dealing with incomplete data and cross-platform applications. In this paper, we propose BotBuster, a social bot detector built with the concept of a mixture of experts approach. Each expert is trained to analyze a portion of account information, e.g. username, and are...

Online social connections occur within a specific conversational context. Prior work in network analysis of social media data attempts to contextualize data through filtering. We propose a method of contextualizing online conversational connections automatically and illustrate this method with Twitter data. Specifically, we detail a graph neural ne...

Past work on key actor detection in the area of terrorism typically focuses on the identification of Threats i.e. users with overt radical signals, or Influencers i.e. users who communicate a high volume of tweets and receive a high volume of replies from their followers. In this work, we expanded the detection of key actors to include Vulnerables,...

The recent COVID-19 outbreak has highlighted the importance of effective communication strategies to control the spread of the virus and debunk misinformation. By using accurate narratives, both online and offline, we can motivate communities to follow preventive measures and shape attitudes toward them. However, the abundance of misinformation sto...

The Twitter social network for each of the top five U.S. Democratic presidential candidates in 2020 was analyzed to determine if there were any differences in the treatment of the candidates. This data set was collected from discussions of the presidential primary between December 2019 through April 2020. It was then separated into five sets, one f...

This paper examines the link between conversational communities on Twitter and their members' expressions of social identity. It specifically tests the presence of community prototypes, or collections of attributes which define a group through meta-contrast: high in-group cohesiveness and high out-group distinctiveness. Analyzing four datasets of p...

The Kremlin’s use of bots and trolls to manipulate the recommendation algorithms of social media platforms is well-documented by many journalists and researchers. However pro-Kremlin manipulation of search engine algorithms has rarely been explored. We examine pro-Kremlin attempts to manipulate search engine results by comparing backlink and keyphr...

Unlabelled: Democracies around the world face the threat of manipulation of their electorates via coordinated online influence campaigns. Researchers have responded by developing valuable methods for finding automated accounts and identifying false information, but these valiant efforts often fall into a cat-and-mouse game with perpetrators who co...

Social media has provided a citizen voice, giving rise to grassroots collective action, where users deploy a concerted effort to disseminate online narratives and even carry out offline protests. Sometimes these collective action are aided by inorganic synchronization, which arise from bot actors. It is thus important to identify the synchronicity...

Data science techniques are powerful tools for extracting knowledge from large datasets. Analyzing the job market by classifying online job advertisements (ads) has recently received much attention. Various approaches for multi-label classification (e.g., self-supervised learning and clustering) have been developed to identify the occupation from a...

This case study investigates a recent Russian disinformation narrative about U.S. biolabs and the development of biological weapons in Ukraine. This disinformation campaign was officially initiated by the Russian government, including the Russian Ministry of Defense, and was disseminated by official state-funded Russian media. In their announcement...

The scale of ransomware damage increases every year. It is difficult to predict the magnitude of the ransomware damage to the organization since many human factors are involved as ransomware infection usually starts with end users downloading malware from the phishing email or message. In this paper, we leveraged OSIRIS (Organization Simulation In...

This paper presents a new computational framework for mapping state-sponsored information operations into distinct strategic units. Utilizing a novel method called multi-view modularity clustering (MVMC), we identify groups of accounts engaged in distinct narrative and network information maneuvers. We then present an analytical pipeline to holisti...

Coordinated disinformation campaigns are used to influence social media users, potentially leading to offline violence. In this study, we introduce a general methodology to uncover coordinated messaging through an analysis of user posts on Parler. The proposed Coordinating Narratives Framework constructs a user-to-user coordination graph, which is...

Social media has provided a citizen voice, giving rise to grassroots collective action, where users deploy a concerted effort to disseminate online narratives and even carry out offline protests. Sometimes these collective action are aided by inorganic synchronization, which arise from bot actors. It is thus important to identify the synchronicity...

Stance detection identifies a person’s evaluation of a subject, and is a crucial component for many downstream applications. In application, stance detection requires training a machine learning model on an annotated dataset and applying the model on another to predict stances of text snippets. This cross-dataset model generalization poses three ce...

This paper investigates how hate speech varies in systematic ways according to the identities it targets. Across multiple hate speech datasets annotated for targeted identities, we find that classifiers trained on hate speech targeting specific identity groups struggle to generalize to other targeted identities. This provides empirical evidence for...

People have consistently had the ability to perceive faces, their emotions, and their expressions. PCs today have similar capabilities. We suggest a model that can identify human faces and categorise facial expressions as happy, angry, sad, neutral, surprised, disgusted, or scared. It involves several stages and is created using a convolutional neu...

In computational social science, two parallel research directions exploring – news consumption patterns and linguistic regularities – have made significant inroads into better understanding complex political polarization in the era of ubiquitous internet. However, little or no literature exists that presented a unified treatment combining both thes...

News articles shared on social media platforms could be framed in ways such that specific points are emphasized or de-emphasized to create confusion on scientific facts. In this work, we use policy frames suggested by Boydstun et al., 2014 to find frames used in over 810k climate change news articles shared on Twitter by news agencies. Moreover, we...

By analyzing tweets sent before and after Twitter users’ first interactions with known low- or high-credibility information sources, we have observed that people who interacted with low-credibility information tended to be more hateful even before that interaction. Such people seemed to further increase their hatefulness only following particularly...

China has embraced the social media domain to promote pro-Chinese narratives and stories in recent years. However, China has increasingly been accused of launching information operations using methods such as bot activity, puppet accounts and other forms of inauthentic activity to amplify pro-Chinese messaging. This paper provides a comprehensive n...

State-led online influence campaigns represent a major frontier in contemporary global politics. Such operations, however, do not take place unopposed and may encounter collective resistance. This study compares two competing influence campaigns during the 2021 Hong Kong Legislative Council (Legco) election: one by the Chinese state seeking to emph...

OSIRIS, Organization Simulation In Response to Intrusion Strategies, is an agent-based simulation framework that models virtual organization composed of end user agents with complex and realistic behavior patterns. The purpose of OSIRIS is to predict and analyze the scale of cyberattack damage on the organization once targeted by cybercriminals wit...

Social media has become an integral component of the modern information system. An average person typically has multiple accounts across different platforms. At the same time, the rise of social media facilitates the spread of online mis/disinformation narratives within and across these platforms. In this study, we characterize the coordinated info...

This paper posits and tests a social cybersecurity framework to detect and characterize online trolling. Using a dataset of online trolling obtained through active learning, we empirically find that troll messages are significantly associated with more abusive language (p<.001), lower cognitive complexity (p<.01), and greater targeting of named ent...

Coordinated campaigns in the digital realm have become an increasingly important area of study due to their potential to cause political polarization and threats to security through real-world protests and riots. In this paper, we introduce a methodology to profile two case studies of coordinated actions in Indonesian Twitter discourse. Combining n...