Himarsha R. Jayanetti

Himarsha R. Jayanetti

Computer Science PhD Student, WS-DL

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About Me

Hello, I am Himarsha R. Jayanetti, a Ph.D. Candidate in Computer Science at Old Dominion University, where I conduct research under the supervision of Dr. Michele C. Weigle and Dr. Michael L. Nelson as a member of the Web Science and Digital Libraries (WSDL) Research Group.

My research interests include web archiving, digital libraries, social media analysis, web science, data science, information retrieval, machine learning, and computational social science. My current dissertation research investigates how social media content extends beyond its native platforms and is integrated into television news broadcasts, providing new perspectives on measuring information reach and influence.

I have authored multiple conference and journal publications and have been recognized with several awards, including the Best Student Paper Award (TPDL 2022), Best Short Paper Award (JCDL 2023), Best Overall Paper and Best Paper in Data Science Track (MSVSCC 2023), and the ODU Computer Science Graduate Society Hackathon Championship (2025). My work has also been supported through competitive travel grants and research opportunities, including internships with Los Alamos National Laboratory (2022) and the Internet Archive as a Google Summer of Code Contributor (2025).

In addition to research, I am committed to teaching, mentoring, and academic service. I have served as a Teaching Assistant for CS 120: Introduction to Information Literacy and Research (Fall 2019; Spring & Fall 2020) and Instructor for CS 450/550 Database Concepts (Spring 2026) and have contributed to the research community through conference program committee service and peer review activities for venues such as JCDL, TPDL, and CIKM.



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portfolio

presentations

2022

  1. “Creating structure in web archives with collections: different concepts from web archivists,” Conference (Short), TPDL ‘22.

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  2. “Robots still outnumber humans in web archives, but less than before,” Conference (Full), TPDL ‘22.

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2023

  1. “Evaluating Social Media Reach via Mainstream Media Discourse,” Workshop/Meeting, ODU CS PhD Gathering.

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  2. “Xenophobic Events vs. Refugee Population–Using GDELT to Identify Countries with Disproportionate Coverage,” Conference (Full/Poster), SBP BRiMS ‘23.

  3. “Less than 4% of Archived Instagram Account Pages for the Disinformation Dozen are Replayable,” Conference (Short), JCDL ‘23.

  4. “Exploring Xenophobic Events through GDELT Data Analysis,” Student Conference (Full), MSVSCC ‘23.

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  5. “Supporting Account-based Queries for Archived Instagram Posts,” MS thesis defense, ODU CS.

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2024

  1. “Evaluating Social Media Reach via Mainstream Media Discourse,” Conference (DC), CIKM ‘24.

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  2. “How Large a Footprint Do the Residents of Informal Settlements Have in Social Media and News Outlets?,” Workshop/Meeting, Trust & Influence Program Review - AFOSR.

2025

  1. “Tracking Political Trends Around US Presidential Election,” Workshop/Meeting, ODU CSGS Hackathon.

  2. “Infrastructure for Tracking Information Flow from Social Media to U.S. TV News,” Conference (Student Research Shorts), CAPWIC ‘25.

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2026

  1. “Infrastructure for Tracking Information Flow from Social Media to U.S. TV News,” WS-DL Research Expo, ODU CS.

  2. “Infrastructure for Tracking Information Flow from Social Media to U.S. TV News,” PhD Proposal, ODU CS.

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projects

M.S. Thesis

2019 -- 2023

My master’s thesis titled, “Supporting Account-based Queries for Archived Instagram Posts”. We addressed a fundamental challenge in social media preservation: valuable Instagram content exists in web archives, but users often cannot discover it because they do not know the original post URLs. I developed two approaches to enable users to retrieve archived Instagram posts associated with a specific account, one leveraging WARC revisit records within the Internet Archive and the other using an external index mapping Instagram accounts to their posts. I implemented and evaluated both approaches, highlighting their practical advantages and limitations for web archives.

Extracting Metadata from Scanned ETDs

2020

We developed a conditional random field (CRF) model that combines text-based and visual features to automatically extract metadata from scanned Electronic Theses and Dissertations (ETDs). We evaluated our method using 500 human-validated ETD cover pages. The model significantly outperformed text-only and heuristic approaches, achieving 81.3%–96% F1 scores across seven metadata fields.

Adverse Effects of Twitter’s UI change on Web Archives

2021

We examined the challenges of preserving Twitter content in web archives following Twitter’s June 2020 UI change. We found that many archives could not properly capture the new interface, leading to missing or incomplete content and potentially inaccurate historical records. Using the personal Twitter account of the 45th U.S. President, @realDonaldTrump, we identified missing evidence of misinformation labels and temporal inconsistencies in archived pages. The goal of this study is to caution the researchers to critically evaluate archived social media data before drawing historical conclusions.

DSA Project

2021

This project developed storytelling solutions to improve the discovery and understanding of web archive collections. I contributed to several components of the DSA project, including AIU, Raintale, and MementoEmbed. AIU is a Python library that gathers seed URLs and metadata from web archive collections such as Archive-It, Pandora, and Trove using APIs and screen scraping. MementoEmbed generates archive-aware cards for individual mementos, while Raintale organizes these cards into engaging, shareable stories. Taken together, these tools help transform large and complex web archive collections into accessible and meaningful experiences for archivists, researchers, and the public.

What’s Missing? Innovating Interdisciplinary Methods for Hard-to-Reach Environments

2022 -- 2025

This was a large interdisciplinary research project which was funded by the U.S. Department of Defense Minerva Research Initiative investigating methods for studying hard-to-reach environments (Khayelitsha Site-C, South Africa and Villa Caracas, Colombia). The project brought together an international team across the U.S., Canada, Norway, and Colombia. The work examines methodological and epistemological gaps when only certain research approaches are feasible. Our component focuses on analyzing these sites using public data sources such as global news and social media, alongside complementary methods including surveys, visual sociology, and citizen science across collaborating teams. The project was later discontinued before completion.

Data Science for Social Good Project

2022 -- 2023

This project is titled “Data Science for Social Good: Mining and Visualizing Worldwide News to Monitor Xenophobic Violence” and was funded by the 2022-2023 ODU Data Science Seed Funding Program. We examined xenophobic events related to refugees and migration using the GDELT 2.0 database and APIs. Our research used visualizations to explore patterns in media coverage through two case studies. We also discussed the data analysis process and the challenges of working with GDELT data and its tools.

ETD Data Enhancement

2022

We developed MetaEnhance, an AI-based framework for automatically detecting, correcting, and standardizing metadata errors in Electronic Theses and Dissertations (ETDs). Using a benchmark of 500 ETDs, MetaEnhance achieved near-perfect F1-scores for error detection and correctness F1-scores ranging from 0.85 to 1.00 for five of seven fields.

Access Patterns of Robots and Humans in Web Archives

2022

We analyzed human and robot access patterns in web archives using Internet Archive’s Wayback Machine and Portuguese Web Archive access logs from 2012 and 2019. We classified user sessions as human or robot based on browsing behavior and then analyzed them to identify navigation patterns and temporal preferences. The study found that robots dominated archive traffic, accounting for up to 98% of requests, while their access patterns became more varied over time. Both humans and robots showed a strong preference for recently archived web pages.

Analyzing Unnecessary Traffic In Web Archives

2022

Archived web pages can generate repeated, invisible HTTP requests, creating unnecessary traffic and potentially overwhelming web archive servers. Pages requiring frequent updates, such as sports scores or playlists, were especially likely to cause this problem, particularly when missing resources produce repeated 404 errors. We proposed to use Cache-Control headers to cache 404 responses, preventing unnecessary requests from reaching the archive server. Our results showed that this approach can reduce wasted network and computational resources during archival replay.

Ph.D. Dissertation

2023 -- Present

This study examines how social media content extends beyond its platform and is integrated into television news. Existing research largely measures impact through intra-platform engagement, overlooking television’s role as a widely consumed and more trusted medium with a distinct audience. As a result, additional reach and influence of social media content beyond its native platform remain significantly underestimated. To address this gap, this work proposes a framework for detecting and analyzing social media references in TV news broadcasts.

publications

2021

  1. Kritika Garg, Himarsha R. Jayanetti, Sawood Alam, Michele C. Weigle, and Michael L. Nelson, “Replaying Archived Twitter: When your bird is broken, will it bring you down?,” In Proceedings of ACM/IEEE Joint Conference on Digital Libraries (JCDL). September 2021, pp. 160-169.    
  2. Muntabir Hasan Choudhury, Himarsha R. Jayanetti, Jian Wu, William A. Ingram, and Edward A. Fox, “Automatic Metadata Extraction Incorporating Visual Features from Scanned Electronic Theses and Dissertations,” In Proceedings of ACM/IEEE Joint Conference on Digital Libraries (JCDL). September 2021, short paper, pp. 230–233.  

2022

  1. Kritika Garg, Himarsha Jayanetti, Sawood Alam, Michele C. Weigle, and Michael L. Nelson, “Caching HTTP 404 Responses Eliminates Unnecessary Archival Replay Requests,” In Proceedings of the International Conference on Asia-Pacific Digital Libraries (ICADL). December 2022.  
  2. Himarsha Jayanetti, Shawn Jones, Martin Klein, Alex Osbourne, Paul Koerbin, Michael L. Nelson, and Michele C. Weigle, “Creating Structure in Web Archives With Collections: Different Concepts From Web Archivists,” In Proceedings of the Theory and Practice of Digital Libraries Conference (TPDL). September 2022, short paper.  
  3. Himarsha Jayanetti, Kritika Garg, Sawood Alam, Michael L. Nelson, and Michele C. Weigle, “Robots Still Outnumber Humans in Web Archives, But Less Than Before,” In Proceedings of the Theory and Practice of Digital Libraries Conference (TPDL). September 2022. Best Student Paper Award.    
  4. Kritika Garg, Himarsha Jayanetti, Sawood Alam, Michele C. Weigle, and Michael L. Nelson, “Optimizing Archival Replay by Eliminating Unnecessary Traffic to Web Archives,” Presented at the ACM/IEEE JCDL 2022 Workshop on Web Archiving and Digital Libraries (WADL), June 2022.  
  5. Himarsha Jayanetti, Kritika Garg, Sawood Alam, Michael L. Nelson, and Michele C. Weigle, “Comparison of Access Patterns of Robots and Humans in Web Archives,” Presented at the ACM/IEEE JCDL 2022 Workshop on Web Archiving and Digital Libraries (WADL), June 2022.  
  6. Shawn M. Jones, Himarsha R. Jayanetti, Alex Osborne, Paul Koerbin, Martin Klein, Michele C. Weigle, and Michael L. Nelson, “The DSA Toolkit Shines Light Into Dark and Stormy Archives,” code{4}lib Journal, No. 53, May 2022.  

2023

  1. Shawn M. Jones, Himarsha R. Jayanetti, Martin Klein, Michele C. Weigle, and Michael L. Nelson, “Synthesizing Web Archive Collections into Big Data: Lessons from Mining Data from Web Archives,” In Proceedings of the Theory and Practice of Digital Libraries Conference (TPDL). September 2023.  
  2. Himarsha R. Jayanetti, Erika Frydenlund, and Michele C. Weigle, “Xenophobic Events vs. Refugee Population – Using GDELT to Identify Countries with Disproportionate Coverage,” Poster presented at the 16th International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRIMS), September 2023.    
  3. Kritika Garg, Himarsha R. Jayanetti, Sawood Alam, Michele C. Weigle, and Michael L. Nelson, “Challenges in replaying archived Twitter pages,” International Journal on Digital Libraries (IJDL), August 2023.  
  4. Haley Bragg, Himarsha Jayanetti, Michael L. Nelson, and Michele C. Weigle, “Less than 4% of Archived Instagram Account Pages for the Disinformation Dozen are Replayable,” In Proceedings of ACM/IEEE Joint Conference on Digital Libraries (JCDL). June 2023, short paper.  
  5. Muntabir Hasan Choudhury, Lamia Salsabil, Himarsha Jayanetti, Jian Wu, William A. Ingram, and Edward A. Fox, “MetaEnhance: Metadata Quality Improvement for Electronic Theses and Dissertations of University Libraries,” In Proceedings of ACM/IEEE Joint Conference on Digital Libraries (JCDL). June 2023, short paper. Best Short Paper Award.    
  6. Himarsha R. Jayanetti, “Supporting Account-Based Queries for Archived Instagram Posts,” Master’s thesis, Old Dominion University, May 2023.  
  7. Himarsha R. Jayanetti, Erika Frydenlund, and Michele C. Weigle, “Exploring Xenophobic Events through GDELT Data Analysis,” Technical report arXiv:2305.01708, Paper presented at the 16th Annual Modeling, Simulation, and Visualization Student Capstone Conference, May 2023. Best Overall Paper, Best Paper in Data Science track Award.    

2024

  1. Himarsha R. Jayanetti, “Evaluating Social Media Reach via Mainstream Media Discourse,” In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (CIKM). October 2024, pp. 5455–5458.  
  2. Himarsha R. Jayanetti, Kritika Garg, Sawood Alam, Michael L. Nelson, and Michele C. Weigle, “Robots still outnumber humans in web archives in 2019, but less than in 2015 and 2012,” International Journal on Digital Libraries (IJDL), March 2024.  

Award Publications

  1. Muntabir Hasan Choudhury, Lamia Salsabil, Himarsha Jayanetti, Jian Wu, William A. Ingram, and Edward A. Fox, “MetaEnhance: Metadata Quality Improvement for Electronic Theses and Dissertations of University Libraries,” In Proceedings of ACM/IEEE Joint Conference on Digital Libraries (JCDL). June 2023, short paper. Best Short Paper Award.    
  2. Himarsha R. Jayanetti, Erika Frydenlund, and Michele C. Weigle, “Exploring Xenophobic Events through GDELT Data Analysis,” Technical report arXiv:2305.01708, Paper presented at the 16th Annual Modeling, Simulation, and Visualization Student Capstone Conference, May 2023. Best Overall Paper, Best Paper in Data Science track Award.    
  3. Himarsha Jayanetti, Kritika Garg, Sawood Alam, Michael L. Nelson, and Michele C. Weigle, “Robots Still Outnumber Humans in Web Archives, But Less Than Before,” In Proceedings of the Theory and Practice of Digital Libraries Conference (TPDL). September 2022. Best Student Paper Award.    

Conferences and Workshops (Peer-Reviewed)

  1. Himarsha R. Jayanetti, “Evaluating Social Media Reach via Mainstream Media Discourse,” In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (CIKM). October 2024, pp. 5455–5458.  
  2. Shawn M. Jones, Himarsha R. Jayanetti, Martin Klein, Michele C. Weigle, and Michael L. Nelson, “Synthesizing Web Archive Collections into Big Data: Lessons from Mining Data from Web Archives,” In Proceedings of the Theory and Practice of Digital Libraries Conference (TPDL). September 2023.  
  3. Haley Bragg, Himarsha Jayanetti, Michael L. Nelson, and Michele C. Weigle, “Less than 4% of Archived Instagram Account Pages for the Disinformation Dozen are Replayable,” In Proceedings of ACM/IEEE Joint Conference on Digital Libraries (JCDL). June 2023, short paper.  
  4. Muntabir Hasan Choudhury, Lamia Salsabil, Himarsha Jayanetti, Jian Wu, William A. Ingram, and Edward A. Fox, “MetaEnhance: Metadata Quality Improvement for Electronic Theses and Dissertations of University Libraries,” In Proceedings of ACM/IEEE Joint Conference on Digital Libraries (JCDL). June 2023, short paper. Best Short Paper Award.    
  5. Kritika Garg, Himarsha Jayanetti, Sawood Alam, Michele C. Weigle, and Michael L. Nelson, “Caching HTTP 404 Responses Eliminates Unnecessary Archival Replay Requests,” In Proceedings of the International Conference on Asia-Pacific Digital Libraries (ICADL). December 2022.  
  6. Himarsha Jayanetti, Kritika Garg, Sawood Alam, Michael L. Nelson, and Michele C. Weigle, “Robots Still Outnumber Humans in Web Archives, But Less Than Before,” In Proceedings of the Theory and Practice of Digital Libraries Conference (TPDL). September 2022. Best Student Paper Award.    
  7. Himarsha Jayanetti, Shawn Jones, Martin Klein, Alex Osbourne, Paul Koerbin, Michael L. Nelson, and Michele C. Weigle, “Creating Structure in Web Archives With Collections: Different Concepts From Web Archivists,” In Proceedings of the Theory and Practice of Digital Libraries Conference (TPDL). September 2022, short paper.  
  8. Kritika Garg, Himarsha R. Jayanetti, Sawood Alam, Michele C. Weigle, and Michael L. Nelson, “Replaying Archived Twitter: When your bird is broken, will it bring you down?,” In Proceedings of ACM/IEEE Joint Conference on Digital Libraries (JCDL). September 2021, pp. 160–169.    
  9. Muntabir Hasan Choudhury, Himarsha R. Jayanetti, Jian Wu, William A. Ingram, and Edward A. Fox, “Automatic Metadata Extraction Incorporating Visual Features from Scanned Electronic Theses and Dissertations,” In Proceedings of ACM/IEEE Joint Conference on Digital Libraries (JCDL). September 2021, short paper, pp. 230–233.  

Journals and Magazines

  1. Himarsha R. Jayanetti, Kritika Garg, Sawood Alam, Michael L. Nelson, and Michele C. Weigle, “Robots still outnumber humans in web archives in 2019, but less than in 2015 and 2012,” International Journal on Digital Libraries (IJDL), March 2024.  
  2. Kritika Garg, Himarsha R. Jayanetti, Sawood Alam, Michele C. Weigle, and Michael L. Nelson, “Challenges in replaying archived Twitter pages,” International Journal on Digital Libraries (IJDL), August 2023.  
  3. Shawn M. Jones, Himarsha R. Jayanetti, Alex Osborne, Paul Koerbin, Martin Klein, Michele C. Weigle, and Michael L. Nelson, “The DSA Toolkit Shines Light Into Dark and Stormy Archives,” code{4}lib Journal, No. 53, May 2022.  

Other (Poster Presentations, Dissertation, Misc)

  1. Himarsha R. Jayanetti, Erika Frydenlund, and Michele C. Weigle, “Xenophobic Events vs. Refugee Population – Using GDELT to Identify Countries with Disproportionate Coverage,” Poster presented at the 16th International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRIMS), September 2023.    
  2. Himarsha R. Jayanetti, “Supporting Account-Based Queries for Archived Instagram Posts,” Master’s thesis, Old Dominion University, May 2023.  
  3. Himarsha R. Jayanetti, Erika Frydenlund, and Michele C. Weigle, “Exploring Xenophobic Events through GDELT Data Analysis,” Technical report arXiv:2305.01708, Paper presented at the 16th Annual Modeling, Simulation, and Visualization Student Capstone Conference, May 2023. Best Overall Paper, Best Paper in Data Science track Award.    
  4. Kritika Garg, Himarsha Jayanetti, Sawood Alam, Michele C. Weigle, and Michael L. Nelson, “Optimizing Archival Replay by Eliminating Unnecessary Traffic to Web Archives,” Presented at the ACM/IEEE JCDL 2022 Workshop on Web Archiving and Digital Libraries (WADL), June 2022.  
  5. Himarsha Jayanetti, Kritika Garg, Sawood Alam, Michael L. Nelson, and Michele C. Weigle, “Comparison of Access Patterns of Robots and Humans in Web Archives,” Presented at the ACM/IEEE JCDL 2022 Workshop on Web Archiving and Digital Libraries (WADL), June 2022.  

Recent Publications and Talks

  1. Himarsha R. Jayanetti, “Evaluating Social Media Reach via Mainstream Media Discourse,” In Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (CIKM). October 2024, pp. 5455–5458.  
  2. Himarsha R. Jayanetti, Kritika Garg, Sawood Alam, Michael L. Nelson, and Michele C. Weigle, “Robots still outnumber humans in web archives in 2019, but less than in 2015 and 2012,” International Journal on Digital Libraries (IJDL), March 2024.  
  3. Shawn M. Jones, Himarsha R. Jayanetti, Martin Klein, Michele C. Weigle, and Michael L. Nelson, “Synthesizing Web Archive Collections into Big Data: Lessons from Mining Data from Web Archives,” In Proceedings of the Theory and Practice of Digital Libraries Conference (TPDL). September 2023.  
  4. Himarsha R. Jayanetti, Erika Frydenlund, and Michele C. Weigle, “Xenophobic Events vs. Refugee Population – Using GDELT to Identify Countries with Disproportionate Coverage,” Poster presented at the 16th International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRIMS), September 2023.    
  5. Kritika Garg, Himarsha R. Jayanetti, Sawood Alam, Michele C. Weigle, and Michael L. Nelson, “Challenges in replaying archived Twitter pages,” International Journal on Digital Libraries (IJDL), August 2023.  
  6. Haley Bragg, Himarsha Jayanetti, Michael L. Nelson, and Michele C. Weigle, “Less than 4% of Archived Instagram Account Pages for the Disinformation Dozen are Replayable,” In Proceedings of ACM/IEEE Joint Conference on Digital Libraries (JCDL). June 2023, short paper.  
  7. Muntabir Hasan Choudhury, Lamia Salsabil, Himarsha Jayanetti, Jian Wu, William A. Ingram, and Edward A. Fox, “MetaEnhance: Metadata Quality Improvement for Electronic Theses and Dissertations of University Libraries,” In Proceedings of ACM/IEEE Joint Conference on Digital Libraries (JCDL). June 2023, short paper. Best Short Paper Award.    
  8. Himarsha R. Jayanetti, Erika Frydenlund, and Michele C. Weigle, “Exploring Xenophobic Events through GDELT Data Analysis,” Technical report arXiv:2305.01708, Paper presented at the 16th Annual Modeling, Simulation, and Visualization Student Capstone Conference, May 2023. Best Overall Paper, Best Paper in Data Science track Award.    

talks

teaching