DDIHTS • Data-Driven Innovations for Health, Technology, and Society

Data-Driven Innovations for Health, Technology and Society (DDIHTS) Lab

23

Publications

Peer-reviewed papers co-authored by students across conferences and journals in AI, Machine Learning, NLP, Data Science, and HCI since 2021.

27

Student Co-Authors

Students co-lead studies that address pressing societal challenges.

15

International Conferences

Presentations in leading conferences such as IEEE CCWC, HCII, IHIET, IHIET-AI, CSSE, and more.

11

Open-Access Datasets

Publicly available datasets supporting global research in AI, machine learning, and natural language processing.

Alumni at companies (including)

Google Apple Seagate Technology VFS Global Siemens VIVA Finance Intercontinental Exchange …and more

Alumni at Graduate Programs (including)

Northwestern University New York University Tufts University Emory University …and more

Meet the Principal Investigator

Dr. Nirmalya Thakur is an Assistant Professor in the Department of Electrical Engineering and Computer Science at the South Dakota School of Mines and Technology. He completed his PhD at the University of Cincinnati, where he received the Dean’s Fellowship, the Distinguished Thesis Award, the Interdisciplinary Research Fellowship, the Risk Management Awareness Award, and the Engineer of the Month Award. His research interests include Big Data, Data Analysis, Human-Computer Interaction, Machine Learning, and Natural Language Processing. He has co-authored over 50 peer-reviewed publications in leading journals and conferences, focusing on addressing critical societal challenges through innovative, data-driven, and impactful solutions. He has been interviewed by IEEE TV, featured on the cover page of Millennium Magazine, in the American Scientist Magazine, on Yahoo News, on Business Insider, and across other outlets. Dr. Thakur was recognized by the IEEE Computer Society as one of the Top 30 Early Career Professionals of 2024.

Official Website of Dr. Nirmalya Thakur

Open Positions

DDIHTS is actively seeking dedicated and motivated students to join our team.

Master’s Position (MS)

Join an ongoing research project at the intersections of Data Mining, Machine Learning, and Natural Language Processing.

Analyze and interpret public discourse on social media platforms such as X (formerly Twitter) and YouTube.
Opportunity to write a thesis built around real-world, high-impact datasets.

Data Mining Machine Learning NLP

Undergraduate Research Opportunity

Work at the intersections of Big Data, Artificial Intelligence, and Data Analysis.

Prototype and extend state-of-the-art Large Language Models (e.g., ChatGPT and beyond).
Hands-on experience with dataset curation, evaluation, and model pipelines.

Big Data LLMs Data Analysis

Apply Now

What We Do

At the DDIHTS Lab, research focuses on applying artificial intelligence, machine learning, natural language processing, data science, and human-computer interaction to study how public sentiment, misinformation, fear, and anxiety emerge and evolve during global health crises such as COVID-19, Mpox, Measles, and Disease X. The team examines public discourse across social media platforms including X, YouTube, TikTok, Instagram, and Reddit by conducting sentiment analysis, topic modeling, subjectivity analysis, anxiety detection, and toxicity analysis, to investigate how conversations shift across languages and regions during global health crises. This work reveals how communities respond to public health challenges, how conspiracy theories and fake news spread, how emotional reactions evolve in response to new variants of a virus, policy updates, or developments in outbreaks, and how early indicators of misinformation or social resistance can be detected. The lab also develops solutions for healthy aging through assistive technologies for smart homes, including activity recognition, fall detection, and emotion-aware systems, to promote independence and enhance the quality of life for older adults.

Watch a brief overview of the DDIHTS Lab in the video below.

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Social Media Analytics & Insights

Analyzing discourse across social media platforms to analyze sentiment dynamics, detect toxicity, and map the trajectory of emerging narratives.

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Digital Epidemiology from Social Media

Using real-time social media intelligence to detect early indicators of outbreaks, misinformation surges, and public risk perceptions.

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Healthy Aging & Assistive Intelligence

Developing AI-driven smart-home systems for fall detection, behavior analysis, and activity recommendation that support independent living for older adults.

Lab Location: McLaury 109B, Department of Electrical Engineering and Computer Science, South Dakota School of Mines and Technology

Poster Showcase

A quick peek at a couple of our recent research projects.

Poster for our paper - "Dissemination of Misinformation about COVID-19 on TikTok: A Multimodal Analysis", presented at the HCII 2024 conference in Washington, United States

Poster for our paper - "Systematic Classification of Studies Investigating Social Media Conversations about Long COVID Using a Novel Zero-Shot Transformer Framework", presented at the HCII 2025 conference in Gothenburg, Sweden

Recent News

Success Stories of Current & Former Members of DDIHTS

Student co-authors across premier conferences worldwide.

HCII 2025 – Gothenburg, Sweden IEEE CCWC 2025 – Nevada, United States HCII 2024 – Washington, United States IHIET 2024 – Venice, Italy HCII 2023 – Copenhagen, Denmark CSSE 2022 – Guilin, China IHIET-AI 2022 – Lausanne, Switzerland

Hall of Talent

Publications (2021–Present)

Nirmalya Thakur, Mingchen Shao, Victoria Knieling, Vanessa Su, Andrew Bian, and Hongseok Jeong, "Dynamics of COVID-19 Misinformation: An Analysis of Conspiracy Theories, Fake Remedies, and False Reports", Proceedings of the 27th International Conference on Human-Computer Interaction (HCII 2025), Gothenburg, Sweden, June 22 - June 27, 2024 (link to the publication)
Nirmalya Thakur, Niven Fernandes, and Marc Tchona, "Systematic Classification of Studies Investigating Social Media Conversations about Long COVID Using a Novel Zero-Shot Transformer Framework", Proceedings of the 27th International Conference on Human-Computer Interaction (HCII 2025), Gothenburg, Sweden, June 22 - June 27, 2024 (link to the publication)
Vanessa Su and Nirmalya Thakur, "COVID-19 on YouTube: a Data-Driven Analysis of Sentiment, Toxicity, and Content Recommendations", Proceedings of the 15th Annual Computing and Communication Workshop and Conference (IEEE CCWC 2025) Nevada, United States, January 6-8, 2025 (link to the publication)
Nirmalya Thakur, Kesha A. Patel, Audrey Poon, Shuqi Cui, Nazif Azizi, Rishika Shah, and Riyan Shah, "Quantifying Public Response to COVID-19 Events: Introducing the Community Sentiment and Engagement Index", Proceedings of the 15th Annual Computing and Communication Workshop and Conference (IEEE CCWC 2025) Nevada, United States, January 6-8, 2025 (link to the publication)
Nirmalya Thakur, Kesha A. Patel, Audrey Poon, Rishika Shah, Nazif Azizi, and Changhee Han "Investigation of the Global Fear Associated with COVID-19 Using Subjectivity Analysis and Deep Learning", Journal of Computation, Volume 12, Issue 6, Article 118 (link to the publication) [J, Impact Factor 1.9]
Nirmalya Thakur, Vanessa Su, Mingchen Shao, Kesha A. Patel, Hongseok Jeong, Victoria Knieling, and Andrew Bian, "A labeled dataset for sentiment analysis of videos on YouTube, TikTok, and other sources about the 2024 outbreak of measles", Proceedings of the 26th International Conference on Human-Computer Interaction (HCII 2024), Washington, United States, June 29 - July 4, 2024 (link to the publication)
Shuqui Cui, Nirmalya Thakur, and Audrey Poon, "Emoji Retrieval from Gibberish or Garbled Social Media Text: A Novel Methodology and A Case Study", Proceedings of the 26th International Conference on Human-Computer Interaction (HCII 2024), Washington, United States, June 29 - July 4, 2024 (link to the publication)
Victoria Knieling and Nirmalya Thakur, "Stress, Anxiety, and Depression in Young Adults: Findings from a User Diversity-based Analysis", Proceedings of the 12th International Conference on Human Interaction and Emerging Technologies (IHIET 2024) in Venice, Italy, August 26-28, 2024 (link to the publication)
Kesha A. Patel and Nirmalya Thakur, "Dissemination of Misinformation about COVID-19 on TikTok: A Multimodal Analysis", Proceedings of the 26th International Conference on Human-Computer Interaction (HCII 2024), Washington, United States, June 29 - July 4, 2024 (link to the publication)
Nirmalya Thakur, Shuqi Cui, Victoria Knieling, Karam Khanna, and Mingchen Shao "Investigation of the Misinformation about COVID-19 on YouTube Using Topic Modeling, Sentiment Analysis, and Language Analysis", Journal of Computation, Volume 12, Issue 2, Article 28 (link to the publication) [J, Impact Factor 1.9]
Nirmalya Thakur, Shuqi Cui, Karam Khanna, Victoria Knieling, Yuvraj Nihal Duggal, and Mingchen Shao "Investigation of the Gender-Specific Discourse about Online Learning during COVID-19 on Twitter using Sentiment Analysis, Subjectivity Analysis, and Toxicity Analysis", Journal of Computers, Volume 12, Issue 11, Article 221 (link to the publication) [J, Impact Factor 2.6]
Nirmalya Thakur, Kesha A. Patel, Audrey Poon, Rishika Shah, Nazif Azizi, and Changhee Han "A Comprehensive Analysis and Investigation of the Public Discourse on Twitter about Exoskeletons from 2017 to 2023", Journal of Future Internet, Volume 15, Issue 10, Article 346 (link to the publication) [J, Impact Factor 2.8]
Nirmalya Thakur, Shuqi Cui, Kesha A. Patel, Isabella Hall, and Yuvraj Nihal Duggal "A Large-Scale Dataset of Search Interests related to Disease X originating from different Geographic Regions", Journal of Data, Volume 8, Issue 11, Article 163 (link to the publication) [J, Impact Factor 2.2]
Nirmalya Thakur, Shuqi Cui, Kesha A. Patel, Nazif Azizi, Victoria Knieling, Changhee Han, Audrey Poon, and Rishika Shah "Marburg Virus Outbreak and a New Conspiracy Theory: Findings from a Comprehensive Analysis and Forecasting of Web Behavior", Journal of Computation, Volume 11, Issue 11, Article 234 (link to the publication) [J, Impact Factor 1.9]
Nirmalya Thakur, Yuvraj Nihal Duggal, and Zihui Liu, "Analyzing Public Reactions, Perceptions, and Attitudes during the MPox Outbreak: Findings from Topic Modeling of Tweets", Journal of Computers, Volume 12, Issue 10, Article 191 (link to the publication) [J, Impact Factor 2.6]
Nirmalya Thakur, Karam Khanna, Shuqi Cui, Nazif Azizi, and Zihui Liu, "Mining and Analysis of Search Interests related to Online Learning Platforms from Different Countries since the Beginning of COVID-19", Proceedings of the 25th International Conference on Human-Computer Interaction (HCII 2023), Copenhagen, Denmark, July 23-28, 2023 (link to the publication)
Nirmalya Thakur, Hazel Cho, Haokun Cheng, and Hyunji Lee, "Analysis of User Diversity-based Patterns of Public Discourse on Twitter in the Context of Mental Health during Online Learning Due to COVID-19", Proceedings of the 25th International Conference on Human-Computer Interaction (HCII 2023), Copenhagen, Denmark, July 23-28, 2023 (link to the publication)
Nirmalya Thakur, Isabella Hall, and Chia Y. Han,"A Comprehensive Study to Analyze Trends in Web Search Interests Related to Fall Detection Before and After COVID-19", Proceedings of the 5th International Conference on Computer Science and Software Engineering (CSSE 2022), Guilin, China, October 21-23, 2022 (link to the publication)
Nirmalya Thakur, Isabella Hall, and Chia Y. Han, "Investigating the Emergence of Online Learning in Different Countries using the 5 W’s and 1 H Approach", Proceedings of the 7th International Conference on Human Interaction & Emerging Technologies: Artificial Intelligence & Future Applications (IHIET-AI 2022), Lausanne, Switzerland, April 21-23, 2022 (link to the publication)
Nirmalya Thakur, Saumick Pradhan, and Chia Y. Han, "Investigating the impact of COVID-19 on Online Learning-based Web Behavior", Proceedings of the 7th International Conference on Human Interaction & Emerging Technologies: Artificial Intelligence & Future Applications (IHIET-AI 2022), Lausanne, Switzerland, April 21-23, 2022 (link to the publication)
Isabella Hall, Nirmalya Thakur, and Chia Y. Han, "Trends in Remote Learning-based Google Shopping in the United States due to COVID-19", Proceedings of the 7th International Conference on Human Interaction & Emerging Technologies: Artificial Intelligence & Future Applications (IHIET-AI 2022), Lausanne, Switzerland, April 21-23, 2022 (link to the publication)
Nirmalya Thakur, Cat Luong, and Chia Y. Han, "An Approach to Investigate Public Opinion, Views, and Perspectives Towards Exoskeleton Technology", Proceedings of the 7th International Conference on Human Interaction & Emerging Technologies: Artificial Intelligence & Future Applications (IHIET-AI 2022), Lausanne, Switzerland, April 21-23, 2022 (link to the publication)