Munjung Kim

PhD Student in Informatics (Complex Networks and Systems) · Indiana University Bloomington
munjkim@iu.edu

Hi! I am a second year PhD student in the Department of Informatics (specializing in Complex Network Systems) at Indiana University Bloomington. I am advised by Yong-Yeol Ahn. Before this, I was an undergraduate at Pohang University of Science and Technology (POSTECH).

My research focuses on understanding the mechanisms through which human innovation arises, scientific fields evolve, and scientific theories are formulated. I use various computational methods for my studies such as neural network embedding, language model, and network analysis.

I'm currently engaged in improving or devising methods for quantifying diverse characteristics of scientific works (such as novelty, disruptiveness, etc.) and analyzing the underlying dynamics that govern these traits. My interests also extends to the realm of philosophy of science, where I explore inquiries such as whether scientific progress brings us closer to truth, how the relationship between science and truth changes depending on different scientific methods, and the distinctions that science apart from non-science. Through my studies, I aim to enhance the practices of scientific communities, foster improved scientific methodologies, and potentially pave the way for automated scientific procedures.


Science of Science · Neural Network Embedding · Language Models (LMs)

Recent News

June 2024 I will join Nokia Bell Labs as an intern

July 2023 I gave a poster presentation in ICS2S2

July 2023 I gave an oral presentation in Netsci 2023

June 2023 I joined Santa Fe Institute Complex System Summer School

Projects & Papers

Quantifying Disruptiveness using neural embedding method


Science and technology often revolve around development and disruption, where works can enhance existing knowledge (development) or revolutionize fields (disruption). Due to the significant impact of disruptive innovations and the decline in such breakthroughs, there's growing interest in quantifying two characteristics and comprehending the factors that drive them. Although the disruption index (D) proposed by Funk and Owen-Smith played a key role in exploring disruptive innovations, its characteristics and limitations remain unclear. Here, we introduce a graph embedding approach to quantify disruptiveness and demonstrate that our measure outperforms the original disruption index in multiple tasks. Our measure shares the same idea with the disruption index—because disruptive papers create a new knowledge space, the papers that cite the disruptive papers are much less likely to cite the references of the disruptive papers. We leverage the fact that the target and context vectors that node2vec (word2vec) learns have different semantics: by restricting the training context to only one side of the target node, we can learn the context of citations and that of references separately.

[abstract]

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Quantifying topic diversity and disparity using neural embedding methods


Citation count is a popular index for assessing scientific papers. However, it depends on not only the quality of a paper but also various factors, such as conventionality, journal, team size, career age, and gender. Here, we examine the extent to which the conventionality of a paper is related to its citation count by using our measure, topic disparity. The topic disparity is the cosine distance between a paper and its discipline on a neural embedding space. Using this measure, we show that the topic disparity is negatively associated with citation count, even after controlling journal impact, team size, and the career age and gender of the first and last authors. This result indicates that less conventional research tends to receive fewer citations than conventional research. The topic disparity can be used to complement citation count and to recommend papers at the periphery of a discipline because of their less conventional topics.

[paper]

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Experience

Research Assistant

Indiana University Bloomington

- Researching application and modification of current neural embedding methods to the quantification of disruptiveness of scientific works, entropy of scientific fields, and mobility of science.

- Proposed new model to measure disruptiveness of scientific papers.

- Found the unviersal mechansims under the demarcation of scientific fields.

- Conducting research under Prof.’s Yong-Yeol Ahn at IUB funded by Science Genome project

Aug 2022 - Present

Research Assistant

Pohang University of Science and Technology

- Quantified the diversity of research topics using doc2vec

- Collected and parsed data of reports from South Korea policy research institutes, assessed the correlation between the number of researchers from external affiliations and topic diversity

- Quantified the topic disparity (unconventionality) of papers from Microsoft Academic Graph dataset and PLOS ONE dataset using sBERT

- Published a paper on the relationship between citation counts and topci disparity.

May 2019 – Dec 2022

International undergraduate summer research fellow

Indiana University Bloomington

- Found methods for assessing behavioral accountability of brain networks

- Compared behavioral predictability between three types of brain networks using linear methods in machine learning

Apr 2020 – Aug 2021

Quality Assurance Intern

Sk Hynix

- Assisted monitoring the quality of semi-conductors

Dec 2019 - Jan 2020

Education

Indiana University

Doctor of Philosophy, Informatics
Advisor : Yong-Yeol Ahn
August 2022 - Present

Pohang University of Science and Technology

Bachelor of Science, Physics
Feb 2017 - Dec 2021

Skills

Computer Language & Operating Systems

    Pythons, R, Matlab,C, C++, HTML, CSS, UNIX Bash, Linux


AI, ML & DS Libraries

    Pytorch, scikit-learn, Numpy, Scipy, Pandas, NetworkX, igraph, gensim, statsmodels, Snakesmake

Awards & Certifications

  • National Scholarship for Excellence (Sci. & Eng.) - Korea Studnet Aid Foundation, $20,000
  • Global Talent Attraction Program, Indiana University Bloomington, $4,000
  • 2 st Bachelor's Thesis Award - Pohang University of Science and Technology
  • Semester of High Honor, 2019, 2020, 2021
  • Senior Mentoring Program Scholarship, 2019, 2020
  • Residential College Advisor Scholarship, 2019