Mayor Inna Gurung Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Graduate Research Assistant
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Biography and Research Information
OverviewAI-generated summary
Mayor Inna Gurung, a Graduate Research Assistant at the University of Arkansas at Little Rock, investigates the diffusion of information and narratives across social media platforms. Her research applies epidemiological models to understand how information spreads, particularly in polarized environments. Gurung's work examines the role of semiotics, including visual media and symbolic signals, in shaping user engagement, emotion, and trust within information campaigns. She has also explored the application of natural language processing techniques, such as GPT-4, in analyzing and understanding online content. Her publications include studies on YouTube's recommendation systems and the contagious nature of narratives. Gurung collaborates with researchers including Nitin Agarwal, Ahmed Al‐Taweel, Md. Monoarul Islam Bhuiyan, and Emmanuel Addai, with whom she shares multiple publications.
Metrics
- h-index: 4
- Publications: 12
- Citations: 44
Selected Publications
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Narrative Diffusion in Social Topologies: A Comparative Study of LLM-Driven Dynamics (2026)
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Competing Narratives on TikTok: Modeling Taiwan’s 2024 Election Dynamics (2026)
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How Do Competing Narratives Spread? A Stance-Based Epidemiological Approach (2026)
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Narrative diffusion in social networks: a survey (2025)
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Examining the role of semiotics in social media-driven information campaigns (2025)
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Modeling polarized information diffusion with SEI(A)I(D)Z: a stance-based epidemiological approach (2025)
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Symbolic signals on Instagram: how visual media shapes engagement, emotion, trust, and diffusion (2025)
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Developing a Stance-induced Epidemiological Model to Examine Polarized Information Contagion (2025)
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Are Narratives Contagious? Modeling Narrative Diffusion Using Epidemiological Theories (2025)
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Exploring Online Video Narratives and Networks Using VTracker (2023)
Collaboration Network
Top Collaborators
- Decoding YouTube's Recommendation System: A Comparative Study of Metadata and GPT-4 Extracted Narratives
- Are Narratives Contagious? Modeling Narrative Diffusion Using Epidemiological Theories
- How does Semiotics Influence Social Media Engagement in Information Campaigns?
- Symbolic signals on Instagram: how visual media shapes engagement, emotion, trust, and diffusion
- Modeling polarized information diffusion with SEI(A)I(D)Z: a stance-based epidemiological approach
Showing 5 of 9 shared publications
- Decoding YouTube's Recommendation System: A Comparative Study of Metadata and GPT-4 Extracted Narratives
- Are Narratives Contagious? Modeling Narrative Diffusion Using Epidemiological Theories
- How does Semiotics Influence Social Media Engagement in Information Campaigns?
- Symbolic signals on Instagram: how visual media shapes engagement, emotion, trust, and diffusion
- Modeling polarized information diffusion with SEI(A)I(D)Z: a stance-based epidemiological approach
- Developing a Stance-induced Epidemiological Model to Examine Polarized Information Contagion
- Exploring Online Video Narratives and Networks Using VTracker
- Exploring Online Video Narratives and Networks Using VTracker
- Exploring Online Video Narratives and Networks Using VTracker
- Decoding YouTube's Recommendation System: A Comparative Study of Metadata and GPT-4 Extracted Narratives
- Symbolic signals on Instagram: how visual media shapes engagement, emotion, trust, and diffusion
- How Do Competing Narratives Spread? A Stance-Based Epidemiological Approach
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