Nitin Agarwal
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View article: PS3N: leveraging protein sequence-structure similarity for novel drug-drug interaction discovery
PS3N: leveraging protein sequence-structure similarity for novel drug-drug interaction discovery Open
Adverse drug events represent a key challenge in public health, especially concerning drug safety profiling and drug surveillance. Drug-drug interactions represent one of the most popular types of adverse drug events. Most computational ap…
View article: Co-commenters as clues: a partial-label approach to detecting anomalous channels on Youtube
Co-commenters as clues: a partial-label approach to detecting anomalous channels on Youtube Open
We propose a semi-supervised approach that finds anomalous YouTube channels by combining co-commenter networks and engagement features. Our method, named SEPS (Semi-Supervised Embedding-based Propagation Scoring), uses a small set of label…
View article: Simulating User Watch-Time to Investigate Bias in YouTube Shorts Recommendations
Simulating User Watch-Time to Investigate Bias in YouTube Shorts Recommendations Open
Short-form video platforms such as YouTube Shorts increasingly shape how information is consumed, yet the effects of engagement-driven algorithms on content exposure remain poorly understood. This study investigates how different viewing b…
View article: Influence of symbolic content on recommendation bias: analyzing YouTube’s algorithm during Taiwan’s 2024 election
Influence of symbolic content on recommendation bias: analyzing YouTube’s algorithm during Taiwan’s 2024 election Open
This study investigates the role of symbolic content, including social, cultural, and political imagery, in shaping algorithmic biases within YouTube’s recommendation system, using the 2024 Taiwanese presidential election as a case study. …
View article: PRISM: Perceptual Recognition for Identifying Standout Moments in Human-Centric Keyframe Extraction
PRISM: Perceptual Recognition for Identifying Standout Moments in Human-Centric Keyframe Extraction Open
Online videos play a central role in shaping political discourse and amplifying cyber social threats such as misinformation, propaganda, and radicalization. Detecting the most impactful or "standout" moments in video content is crucial for…
View article: Modeling polarized information diffusion with SEI(A)I(D)Z: a stance-based epidemiological approach
Modeling polarized information diffusion with SEI(A)I(D)Z: a stance-based epidemiological approach Open
The spread of narratives online has been extensively studied. However, prior research typically relies on metadata and often overlooks the dynamics of post stances. In this paper, we introduce a novel stance-based epidemiological model, wh…
View article: Symbolic signals on Instagram: how visual media shapes engagement, emotion, trust, and diffusion
Symbolic signals on Instagram: how visual media shapes engagement, emotion, trust, and diffusion Open
Throughout history, visual symbols have served as powerful tools for communication, uniting communities, shaping narratives, and driving social movements. From traditional media such as pamphlets and murals to contemporary public art, thes…
View article: Telegram as a Battlefield: Kremlin-Related Communications During the Russia-Ukraine Conflict
Telegram as a Battlefield: Kremlin-Related Communications During the Russia-Ukraine Conflict Open
Telegram emerged as a crucial platform for both parties during the conflict between Russia and Ukraine. Per its minimal policies for content moderation, Pro-Kremlin narratives and potential misinformation were spread on Telegram, while ant…
View article: TriPSS: A Tri-Modal Keyframe Extraction Framework Using Perceptual, Structural, and Semantic Representations
TriPSS: A Tri-Modal Keyframe Extraction Framework Using Perceptual, Structural, and Semantic Representations Open
Efficient keyframe extraction is critical for video summarization and retrieval, yet capturing the full semantic and visual richness of video content remains challenging. We introduce TriPSS, a tri-modal framework that integrates perceptua…
View article: Safeguarding youtube discussions: a framework for detecting anomalous commenter and engagement behaviors
Safeguarding youtube discussions: a framework for detecting anomalous commenter and engagement behaviors Open
In today’s digital landscape, YouTube’s comment sections play an essential role in shaping public opinion and discussions. However, coordinated groups often exploit these platforms to spread misinformation and distort conversations. This s…
View article: Modeling cross-platform narrative templates: a temporal knowledge graph approach
Modeling cross-platform narrative templates: a temporal knowledge graph approach Open
Over the past decade, online social media has grown in size, features, and complexity, providing users with increased satisfaction and prompting many to maintain accounts across multiple platforms. Information actors have also taken advant…
View article: Constructing a multi-theoretical framework for mob modeling
Constructing a multi-theoretical framework for mob modeling Open
As social media has made us more connected, it has also increased our ability to mobilize groups of people and coordinate events, such as mobs. Understanding the motivation of individuals to join such events and the ability to predict the …
View article: A Review on Large Language Models for Visual Analytics
A Review on Large Language Models for Visual Analytics Open
This paper provides a comprehensive review of the integration of Large Language Models (LLMs) with visual analytics, addressing their foundational concepts, capabilities, and wide-ranging applications. It begins by outlining the theoretica…
View article: Developing a network-centric approach for anomalous behavior detection on youtube
Developing a network-centric approach for anomalous behavior detection on youtube Open
As the second most visited website globally, YouTube serves as a central platform for video sharing, entertainment, and information dissemination. However, its expansive and highly active user base also facilitates problematic behavior, pa…
View article: A comparative evaluation of social network analysis tools: performance and community engagement perspectives
A comparative evaluation of social network analysis tools: performance and community engagement perspectives Open
Graphs are increasingly used in research, industry, and government. This has led to a wide range of analytical and graph-processing tools. There are various tools and platforms for graph processing. Over time, diverse systems have emerged,…
View article: Telegram as a Battlefield: Kremlin-related Communications during the Russia-Ukraine Conflict
Telegram as a Battlefield: Kremlin-related Communications during the Russia-Ukraine Conflict Open
Telegram emerged as a crucial platform for both parties during the conflict between Russia and Ukraine. Per its minimal policies for content moderation, Pro-Kremlin narratives and potential misinformation were spread on Telegram, while ant…
View article: Analyzing TikTok’s Role in Mobilizing Dynamics for Information Campaigns during Taiwan’s 2024 Elections
Analyzing TikTok’s Role in Mobilizing Dynamics for Information Campaigns during Taiwan’s 2024 Elections Open
This research investigates and identifies the key mobilizing characteristics in contemporary online information campaigns using novel multi-method socio-computational techniques. Utilizing social theories and network science to study socia…
View article: Examining the role of semiotics in social media-driven information campaigns
Examining the role of semiotics in social media-driven information campaigns Open
The rise of visually driven platforms like Instagram has reshaped how information is shared and understood. This study examines the role of social, cultural, and political (SCP) symbols in Instagram posts during Taiwan’s 2024 election, foc…
View article: How does Semiotics Influence Social Media Engagement in Information Campaigns?
How does Semiotics Influence Social Media Engagement in Information Campaigns? Open
The rise of visually driven social media platforms like Instagram has transformed the way information and narratives are shared. This study explores the impact of social, cultural, and political (SCP) symbols in Instagram images on user en…
View article: Unpacking Algorithmic Bias in YouTube Shorts by Analyzing Thumbnails
Unpacking Algorithmic Bias in YouTube Shorts by Analyzing Thumbnails Open
As digital platforms increasingly shape our online experiences, the influence of recommendation algorithms on user behavior becomes ever more significant. This research delves into the biases inherent in YouTube Shorts' recommendation algo…
View article: Modeling Cross-Platform Narratives Templates: A Temporal Knowledge Graph Approach
Modeling Cross-Platform Narratives Templates: A Temporal Knowledge Graph Approach Open
Over the past decade, online social media has grown in size, features, and complexity, providing users with increased satisfaction and prompting many to maintain accounts across multiple platforms. Information actors have also taken advant…
View article: The bias beneath: analyzing drift in YouTube’s algorithmic recommendations
The bias beneath: analyzing drift in YouTube’s algorithmic recommendations Open
In today’s digital world, understanding how YouTube’s recommendation systems guide what we watch is crucial. This study dives into these systems, revealing how they influence the content we see over time. We found that YouTube’s algorithms…
View article: A Comparative Evaluation of Social Network Analysis Tools: Performance and Community Engagement Perspectives
A Comparative Evaluation of Social Network Analysis Tools: Performance and Community Engagement Perspectives Open
Graphs are increasingly used in research, industry, and government. This has led to a wide range of analytical and graph-processing tools. There are various tools and platforms for graph processing. Many network based platforms, tools and …
View article: KG-CFSA: a comprehensive approach for analyzing multi-source heterogeneous social network knowledge graph
KG-CFSA: a comprehensive approach for analyzing multi-source heterogeneous social network knowledge graph Open
Analyzing opinions, extracting and modeling information, and performing network analysis in online information studies are challenging tasks with multi-source social network data. This complexity arises from the difficulty in harnessing da…
View article: Reducing COVID-19 Misinformation Spread by Introducing Information Diffusion Delay Using Agent-based Modeling
Reducing COVID-19 Misinformation Spread by Introducing Information Diffusion Delay Using Agent-based Modeling Open
With the explosive growth of the Coronavirus Pandemic (COVID-19), misinformation on social media has developed into a global phenomenon with widespread and detrimental societal effects. Despite recent progress and efforts in detecting COVI…
View article: Evaluating collective action theory-based model to simulate mobs
Evaluating collective action theory-based model to simulate mobs Open
A mob is an event that is organized via social media, email, SMS, or other forms of digital communication technologies in which a group of people (who might have an agenda) get together online or offline to collectively conduct an act and …
View article: Evaluating Bias and Fairness in AI: An Analysis of YouTube’s Recommendation Algorithm and its Impact on Geopolitical Discourse
Evaluating Bias and Fairness in AI: An Analysis of YouTube’s Recommendation Algorithm and its Impact on Geopolitical Discourse Open
Exposure to online information is often determined by recommendation algorithms that introduce unintended biases when information system platforms attempt to deliver content that is engaging and relevant to their users. Further investigati…
View article: Reducing COVID-19 Misinformation Spread by Introducing Information Diffusion Delay Using Agent-based Modeling
Reducing COVID-19 Misinformation Spread by Introducing Information Diffusion Delay Using Agent-based Modeling Open
With the explosive growth of the Coronavirus Pandemic (COVID-19), misinformation on social media has developed into a global phenomenon with widespread and detrimental societal effects. Despite recent progress and efforts in detecting COVI…
View article: Decoding YouTube's Recommendation System: A Comparative Study of Metadata and GPT-4 Extracted Narratives
Decoding YouTube's Recommendation System: A Comparative Study of Metadata and GPT-4 Extracted Narratives Open
YouTube's recommendation system is integral to shaping user experiences by suggesting content based on past interactions using collaborative filtering techniques. Nonetheless, concerns about potential biases and homogeneity in these recomm…