Nitin Agarwal Institution-verified
Sourced from institutional research profiles (UAMS TRI or ARA).
COSMOS Research Center - Social Media Analytics and Socio-Cognitive Security
faculty
Research Areas
Links
Biography and Research Information
OverviewAI-generated summary
Nitin Agarwal is the founding director of the Collaboratorium for Social Media and Online Behavioral Studies (COSMOS) and the Jerry L. Maulden-Entergy Endowed Chair and Distinguished Professor of Information Science at the University of Arkansas – Little Rock. He also holds a faculty fellowship at the International Computer Science Institute at the University of California - Berkeley.
His research focuses on understanding digital and cyber social behaviors that emerge on contemporary information and communication platforms. Within COSMOS, Agarwal leads projects funded by federal agencies such as the Department of Defense, DARPA, the Department of State, and the National Science Foundation, totaling over $25 million. He also plays a role in the partnership between UA Little Rock and the Department of Homeland Security. Agarwal has developed publicly available social media analysis tools, including Blogtracker and YouTubeTracker, which have been utilized by organizations like NATO Strategic Communications and Public Affairs, European Defense agencies, the Australian Defense Science and Technology Agency, the Singapore government, and the Arkansas Attorney General’s office.
Agarwal's work has resulted in 318 publications and over 4,155 citations, with an h-index of 30. He is recognized as an ARA Academy member (ARA Scholar) in the research area of Cyber Social Computing and is considered a highly cited researcher.
Metrics
- h-index: 49
- Publications: 644
- Citations: 9,032
Selected Publications
-
Toxicity-Driven Behavioral Homogenization in Multilayer Political Networks: Cross-Dimensional Coupling During Russia-Ukraine Conflict (2026)
-
Attraction and retention dynamics in recommendation graphs: a cross-dataset analysis using uniform and degree-biased random walks (2026)
-
Weighted Focal Structure Analysis for Coordinated Toxicity Propagation in Social Networks (2026)
-
CI-FSA: Toward Scalable Discovery of Influential Groups in Social Networks (2026)
-
Narrative Diffusion in Social Topologies: A Comparative Study of LLM-Driven Dynamics (2026)
-
The Network Effect of Shared Grievances: Measuring Collective Concern of Tariff Policy (2026)
-
Modeling the Propagation Dynamics of Visual Elements with Epidemiological Frameworks (2026)
-
TrapIntensity: Quantifying Structural Entrapment via Hop-Aware Attraction and Retention (2026)
-
Competing Narratives on TikTok: Modeling Taiwan’s 2024 Election Dynamics (2026)
-
How Tariff War Discourse Spreads on Social Media? A Study of Narrative Outbreak (2026)
-
Optimizing Focal Toxic Structure Selection for Social Network Disruption: A WFSA-Integer Programming Approach (2026)
-
Persuasive Pathways Into Content Traps: The Role of Persuasive Features in Structuring Algorithmic Content Cycles (2026)
-
How Far Is Too Far? Modeling User Attraction Pathways in Recommendation Networks via Random Walk Variants (2026)
-
Large-scale toxicity intervention in social networks: evaluating integer programming-optimized focal toxic structures (2026)
-
Identifying cohesive narrative formations in cross-platform trade-war discourse using weighted contextual focal structures analysis (2026)
ARA Academy 2018 ARA Scholar
Dr. Agarwal directs the Collaboratorium for Social Media and Online Behavioral Studies (COSMOS). His work centers on cyber social behaviors in modern information platforms with applications spanning defense, security, health, business, marketing, finance, and education. His specific areas include cyber information campaigns, social computing, deviant behavior modeling, group dynamics, social-cyber forensics, and privacy.
Policy Impact
Directs the COSMOS research center, attracting defense and security funding for social media analytics research that addresses national cybersecurity priorities from Arkansas.
Growth Areas
['Supply Chain Retail & Consumer Analytics']
Collaboration Network
Top Collaborators
- Examining Multimodel Emotion Assessment and Resonance with Audience on YouTube
- Emotion Assessment of YouTube Videos using Color Theory
- Adopting Parallel Processing for Rapid Generation of Transcripts in Multimedia-rich Online Information Environment
- The bias beneath: analyzing drift in YouTube’s algorithmic recommendations
- Analyzing Bias in Recommender Systems: A Comprehensive Evaluation of YouTube's Recommendation Algorithm
Showing 5 of 11 shared publications
- Characterizing Suspicious Commenter Behaviors
- Identifying Contextualized Focal Structures in Multisource Social Networks by Leveraging Knowledge Graphs
- Contextualizing focal structure analysis in social networks
- Comprehensive decomposition optimization method for locating key sets of commenters spreading conspiracy theory in complex social networks
- Using Computational Social Science Techniques to Identify Coordinated Cyber Threats to Smart City Networks
Showing 5 of 9 shared publications
- Applying diffusion of innovations theory to social networks to understand the stages of adoption in connective action campaigns
- Adopting Parallel Processing for Rapid Generation of Transcripts in Multimedia-rich Online Information Environment
- Analyzing Bias in Recommender Systems: A Comprehensive Evaluation of YouTube's Recommendation Algorithm
- Investigating Bias in YouTube Recommendations: Emotion, Morality, and Network Dynamics in China-Uyghur Content
- Using Computational Social Science Techniques to Identify Coordinated Cyber Threats to Smart City Networks
Showing 5 of 9 shared publications
- Developing a socio-computational approach to examine toxicity propagation and regulation in COVID-19 discourse on YouTube
- Examining Video Recommendation Bias on YouTube
- Applying diffusion of innovations theory to social networks to understand the stages of adoption in connective action campaigns
- Using an Epidemiological Model to Study the Spread of Misinformation during the Black Lives Matter Movement
- Applying an Epidemiological Model to Evaluate the Propagation of Misinformation and Legitimate COVID-19-Related Information on Twitter
Showing 5 of 9 shared publications
- Examining Video Recommendation Bias on YouTube
- Telegram: Data Collection, Opportunities and Challenges
- Assessing Bias in YouTube’s Video Recommendation Algorithm in a Cross-lingual and Cross-topical Context
- Comprehensive decomposition optimization method for locating key sets of commenters spreading conspiracy theory in complex social networks
- Developing an agent-based model to minimize spreading of malicious information in dynamic social networks
Showing 5 of 8 shared publications
- Developing a socio-computational approach to examine toxicity propagation and regulation in COVID-19 discourse on YouTube
- Assessing the influence and reach of digital activity amongst far-right actors: A comparative evaluation of mainstream and ‘free speech’ social media platforms
- A public online resource to track COVID-19 misinfodemic
- Analyzing Cyber Influence Campaigns on YouTube Using YouTubeTracker
- Characterizing video-based online information environment using VTracker
- Emotion Assessment of YouTube Videos using Color Theory
- Telegram: Data Collection, Opportunities and Challenges
- Evaluating Role of Instagram’s Multimedia in Connective Action Leveraging Diffusion of Innovation and Cognitive Mobilization Theories: Brazilian and Peruvian Social Unrest Case Studies
- Characterizing Multimedia Adoption and its Role on Mobilization in Social Movements
- Developing Situational Awareness from Blogosphere: An Australian Case Study
- Identifying Contextualized Focal Structures in Multisource Social Networks by Leveraging Knowledge Graphs
- Modeling cross-platform narrative templates: a temporal knowledge graph approach
- A comparative evaluation of social network analysis tools: performance and community engagement perspectives
- KG-CFSA: a comprehensive approach for analyzing multi-source heterogeneous social network knowledge graph
- Detecting and Measuring Anomalous Behaviors on YouTube
- Social Bots and Their Coordination During Online Campaigns: A Survey
- Examining Video Recommendation Bias on YouTube
- Exploring Bias and Information Bubbles in YouTube’s Video Recommendation Networks
- Assessing Bias in YouTube’s Video Recommendation Algorithm in a Cross-lingual and Cross-topical Context
- Flash mob: a multidisciplinary review
- Using Computational Social Science Techniques to Identify Coordinated Cyber Threats to Smart City Networks
- Studying the Role of Social Bots During Cyber Flash Mobs
- Social Bots and Their Coordination During Online Campaigns: A Survey
- Developing a socio-computational approach to examine toxicity propagation and regulation in COVID-19 discourse on YouTube
- Telegram: Data Collection, Opportunities and Challenges
- Examining Video Recommendation Bias on YouTube
- Assessing Bias in YouTube’s Video Recommendation Algorithm in a Cross-lingual and Cross-topical Context
- Assessing the influence and reach of digital activity amongst far-right actors: A comparative evaluation of mainstream and ‘free speech’ social media platforms
- Identifying Contextualized Focal Structures in Multisource Social Networks by Leveraging Knowledge Graphs
- Visualization of Influential Blog Networks Using BlogTracker
- KG-CFSA: a comprehensive approach for analyzing multi-source heterogeneous social network knowledge graph
- Adopting Parallel Processing for Rapid Generation of Transcripts in Multimedia-rich Online Information Environment
- Analyzing Bias in Recommender Systems: A Comprehensive Evaluation of YouTube's Recommendation Algorithm
- Investigating Bias in YouTube Recommendations: Emotion, Morality, and Network Dynamics in China-Uyghur Content
- Examining Multimodel Emotion Assessment and Resonance with Audience on YouTube
- Evaluating Role of Instagram’s Multimedia in Connective Action Leveraging Diffusion of Innovation and Cognitive Mobilization Theories: Brazilian and Peruvian Social Unrest Case Studies
- Developing Epidemiological Models with Differentiated Infected Intensity
Similar Researchers
Based on overlapping research topics