Debarati Das

200 Union St SE

Minneapolis, Minnesota

I am a Ph.D. candidate in the Minnesota NLP group led by Prof. Dongyeop Kang at the University of Minnesota Twin Cities. I am co-supervised by Prof. Jaideep Srivastava who leads the Data Mining and Research Group (DMR) at the University of Minnesota Twin Cities. I also work as a research assistant to Prof. Jisu Huh, who heads the Minnesota Computational Advertising Laboratory (MCAL).

Broadly, my research aims to combine NLP with computational social science. Specifically, I am interested in learning about people — how user preferences, social cues, and contextual factors influence and drive user behavior — in online social media settings. I am also interested in exploring the stylistic analysis of user text content. I have adopted a variety of deep learning, natural language processing, graph, and statistical methods towards my interest in Computational Social Science.

I obtained my Master’s degree in Computer Science from the University of Minnesota, Twin Cities, and my Bachelor’s degree in Computer science from PES University, Bangalore, India.

news

Dec 15, 2024	🎤 Gave a talk titled “When AI learns to Listen: Generative AI in the Social Sciences” to high school students for the Sparkway Learning PythonAI Workshop 2024.
Nov 04, 2024	🎤 Honored to be a speaker at the Women in AI and DS Conference 2024 and discussed the impact of artifacts in LLM-generated data with an incredibly talented crowd!
Oct 08, 2024	🏆 I received the 2024 AnitaB.org Advancing Inclusion scholarship!
Jul 21, 2024	🥳 Our paper “Publics’ Perceptions of Legitimacy in Corporate Social Advocacy: A Computational Analysis of the Influence of Ideological Congruence” is published in Public Relations Review
Jul 18, 2024	🎤 Gave a talk titled “Beyond Words: Incorporating Graph Data into LLMs for Comprehensive Social System Analysis” at IC2S2 2024! P.S The cheesesteak is just fantastic at Philadelphia 🤤
Jun 16, 2024	✅ Presented my paper “Which Modality should I use – Text, Motif, or Image? : Understanding Graphs with Large Language Models” at NAACL 2024 in Mexico City! [Tweet]
Jun 06, 2024	🥳I am thrilled to be interning at Microsoft Research this summer!
May 10, 2024	🎤 Presented my recent paper on LLM-generated artifacts at Megagon Labs, along with Dongyeop Kang
Apr 22, 2024	🎉 Our abstract “Beyond Words: Incorporating Graph Data into LLMs for Comprehensive Social System Analysis” is selected for oral presentation at IC2S2 2024!
Apr 10, 2024	✅ Passed my Thesis Proposal Exam ✌🏽 One more exam to go until my defense!💪🏼

selected publications

journal

Publics’ perceptions of legitimacy in corporate social advocacy: A computational analysis of the role of ideological congruence

Hao Xu, Debarati Das, Jisu Huh, and 2 more authors

Public Relations Review, 2024

Bib PDF

@article{xu2024publics,
  title = {Publics’ perceptions of legitimacy in corporate social advocacy: A computational analysis of the role of ideological congruence},
  author = {Xu, Hao and Das, Debarati and Huh, Jisu and Rim, Hyejoon and Srivastava, Jaideep},
  journal = {Public Relations Review},
  volume = {50},
  number = {4},
  pages = {102486},
  year = {2024},
  publisher = {Elsevier},
}

preprint

Under the surface: Tracking the artifactuality of llm-generated data

Debarati Das, Karin De Langis, Anna Martin-Boyle, and 8 more authors

arXiv preprint arXiv:2401.14698, 2024

Bib PDF Website

@article{das2024under,
  title = {Under the surface: Tracking the artifactuality of llm-generated data},
  author = {Das, Debarati and De Langis, Karin and Martin-Boyle, Anna and Kim, Jaehyung and Lee, Minhwa and Kim, Zae Myung and Hayati, Shirley Anugrah and Owan, Risako and Hu, Bin and Parkar, Ritik and others},
  journal = {arXiv preprint arXiv:2401.14698},
  year = {2024},
}

conference

Which Modality should I use-Text, Motif, or Image?: Understanding Graphs with Large Language Models

Debarati Das, Ishaan Gupta, Jaideep Srivastava, and 1 more author

In Findings of the Association for Computational Linguistics: NAACL 2024, 2024

Bib PDF Website

@inproceedings{das2024modality,
  title = {Which Modality should I use-Text, Motif, or Image?: Understanding Graphs with Large Language Models},
  author = {Das, Debarati and Gupta, Ishaan and Srivastava, Jaideep and Kang, Dongyeop},
  booktitle = {Findings of the Association for Computational Linguistics: NAACL 2024},
  pages = {503--519},
  year = {2024},
}

conference

Balancing the Effect of Training Dataset Distribution of Multiple Styles for Multi-Style Text Transfer

Debarati Das, David Ma, and Dongyeop Kang

In Findings of the Association for Computational Linguistics: ACL 2023, 2023

Bib PDF

@inproceedings{das2023balancing,
  title = {Balancing the Effect of Training Dataset Distribution of Multiple Styles for Multi-Style Text Transfer},
  author = {Das, Debarati and Ma, David and Kang, Dongyeop},
  booktitle = {Findings of the Association for Computational Linguistics: ACL 2023},
  pages = {3932--3943},
  year = {2023},
}

journal

Scalable clustering by aggregating representatives in hierarchical groups

Wen-Bo Xie, Zhen Liu, Debarati Das, and 2 more authors

Pattern Recognition, 2023

Bib PDF

@article{xie2023scalable,
  title = {Scalable clustering by aggregating representatives in hierarchical groups},
  author = {Xie, Wen-Bo and Liu, Zhen and Das, Debarati and Chen, Bin and Srivastava, Jaideep},
  journal = {Pattern Recognition},
  volume = {136},
  pages = {109230},
  year = {2023},
  publisher = {Elsevier},
}

workshop

Adbert: An effective few shot learning framework for aligning tweets to superbowl advertisements

Debarati Das, Roopana Chenchu, Maral Abdollahi, and 2 more authors

In Proceedings of the Eighth Workshop on Noisy User-generated Text (W-NUT 2022), 2022

Bib PDF

@inproceedings{das2022adbert,
  title = {Adbert: An effective few shot learning framework for aligning tweets to superbowl advertisements},
  author = {Das, Debarati and Chenchu, Roopana and Abdollahi, Maral and Huh, Jisu and Srivastava, Jaideep},
  booktitle = {Proceedings of the Eighth Workshop on Noisy User-generated Text (W-NUT 2022)},
  pages = {171--179},
  year = {2022},
}

journal

Influence of Consumers’ Temporary Affect on Ad Engagement: A Computational Research Approach

Xinyu Lu, Debarati Das, Jisu Huh, and 1 more author

Journal of Advertising, 2022

Bib PDF

@article{lu2022influence,
  title = {Influence of Consumers’ Temporary Affect on Ad Engagement: A Computational Research Approach},
  author = {Lu, Xinyu and Das, Debarati and Huh, Jisu and Srivastava, Jaideep},
  journal = {Journal of Advertising},
  volume = {51},
  number = {3},
  pages = {352--368},
  year = {2022},
  publisher = {Taylor \& Francis},
}

conference

A computational analysis of Mahabharata

Debarati Das, Bhaskarjyoti Das, and Kavi Mahesh

In Proceedings of the 13th International Conference on Natural Language Processing, 2016

Bib PDF

@inproceedings{das2016computational,
  title = {A computational analysis of Mahabharata},
  author = {Das, Debarati and Das, Bhaskarjyoti and Mahesh, Kavi},
  booktitle = {Proceedings of the 13th International Conference on Natural Language Processing},
  pages = {219--228},
  year = {2016},
}