Please visit the link at Google Scholar
for more information
2023
User-Chatbot Conversations During the COVID-19 Pandemic: A Study Based on Topic Modeling and Sentiment Analysis
H. Chin, G. Lima, M. Shin, A. Zhunis, C. Cha, J. Choi, and M. Cha, [In Journal of Medical Internet Research (JMIR), To Appear]
Multi-Stage Learning for Hierarchical Tie Valence Prediction
K. Singh, S. Lee, G. Labianca, J. M. Fagan, and M. Cha, [In ACM Transactions on Knowledge Discovery from Data (TKDD), To Appear]
2022
Effects of Child Maltreatment on Physical Activity and Sleep in Healthy Adults: A Wearable Device Use Experiment (ko: 건강한 성인에서 아동기 학대 경험이 신체 활동과 수면에 미치는 영향: 웨어러블 디바이스 사용 실험)
M.-S. Kim, S. Park, M. Cha, and S.-W., [In Journal of the Korean Society
of Biological Therapies in Psychiatry, 2022]
Self-explaining deep models with logic rule reasoning
S. Lee, X. Wang, S. Han, X. Yi, X. Xie, M. Cha, [In NeurIPS 2022, November 2022]
Others Are to Blame: A Multi-Faceted View on Whom People Consider Responsible For Online Misinformation
G. Lima, J. Han, M. Cha, [In Proceedings of the ACM on Human-Computer Interaction, CSCW1, November 2022]
Exploring Text Summarization for Fake News Detection
J. Bian, S. Lee, K. Singh, and M. Cha, [In Journal of KIISE, November 2022]
FedX: Unsupervised Federated Learning with Cross Knowledge Distillation
S Han, S Park, F Wu, S Kim, C Wu, X Xie, M Cha, [In Proceedings of the ECCV 2022: 17th European Conference on Computer Vision, October 2022]
Disaster assessment using computer vision and satellite imagery: Applications in water-related building damage detection
D Kim, J Won, E Lee, K Park, J Kim, S Park, H Yang, M Cha, [In Frontiers in Environmental Science, October 2022]
Understanding the Categories and Characteristics of Depressive Moods in Chatbot Data (ko: 챗봇 데이터에 나타난 우울 담론의 범주와 특성의 이해)
H. Chin, C. Jung, G. Baek, C. Cha, J. Choi, and M. Cha, [In KIPS Transactions on Software and
Data Engineering, September 2022]
An Implicit Identity-Extended Data Augmentation for Low-Resolution Face Representation Learning
C.Y. Low, and A. Beng-Jin Teoh, [In IEEE Transactions on Information Forensics and Security, August 2022.]
Downscaling Earth System Models with Deep Learning
S Park, K Singh, A Nellikkattil, E Zeller, TD Mai, M Cha, [In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, August 2022]
The Conflict Between Explainable and Accountable Decision-Making Algorithms
G. Lima, N. Grgić-Hlača, J.K. Jeong, M. Cha, [In FAccT ’22: 2022 ACM Conference on Fairness, Accountability, and Transparency, June 2022]
Emotion Bubbles: Emotional Composition of Online Discourse Before and After the COVID-19 Outbreak
A. Zhunis, G Lima, H. Song, J. Han, M. Cha, [In Proceedings of the ACM Web Conference 2022 (WWW ’22), April 2022]
Using Web Data to Reveal 22-Year History of Sneaker Designs
S. Park, H. Song, S. Han, L. Manovich, B. Weldegebriel, E. Arielli, M. Cha, [In Proceedings of the ACM Web Conference 2022 (WWW ’22), April 2022] Best Paper Candidate
News Comment Sections and Online Echo Chambers: The Ideological Alignment Between Partisan News Stories and Their User Comments
J. Han, Y. Lee, J, Kim, and M. Cha [In Journalism, March 2022]
An EfficientNet-based weighted ensemble model for industrial machine malfunction detection using acoustic signals
B. A. Tama, M. Vania, I. Kim, S. Lim [In IEEE Access, March 2022]
Misinformation, Believability, and Vaccine Acceptance Over 40 Countries: Takeaways From the Initial Phase of The COVID-19 Infodemic
K. Singh, G. Lima, M. Cha, C. Cha, J. Kulshrestha, Y. Ahn, O. Varol [In Plos One, February 2022]
Learning economic indicators by aggregating multi-level geospatial information
S. Park, S. Han, D. Ahn, J. Kim, J. Yang, S. Lee, S. Hong, J. Kim, S. Park, and M. Cha [In proc. of the AAAI Conference on Artificial Intelligence (AAAI), February 2022]
Knowledge Sharing via Domain Adaptation in Customs Fraud Detection
S. Park, S. Kim, and M. Cha [In proc. of the AAAI Conference on Artificial Intelligence (AAAI), February 2022]
QAnon Shifts Into the Mainstream, Remains a Far-Right Ally
S. Zihiri, G. Lima, J. Han, M. Cha, W. Lee [In Heliyon, February 2022]
Active Learning for Human-in-the-Loop Customs Inspection
S. Kim, T. Mai, S. Han, S. Park, T. Nguyen, J. So, K. Singh, M. Cha [In IEEE Transactions on Knowledge and Data Engineering (TKDE), January 2022]
Understanding and identifying the use of emotes in toxic chat on Twitch
J. Kim, D. Wohn, and M. Cha [Online Social Networks and Media, January 2022]
2021
Customs Fraud Detection in the Presence of Concept Drift
T. Mai, K. Hoang, A. Baigutanova, G. Alina, and S. Kim [Workshop on Incremental Classification and Clustering, Concept Drift, Novelty Detection in Big/Fast Data Context in conjunction with IEEE International Conference on Data Mining, December 2021]
Elsa: Energy-based Learning for Semi-supervised Anomaly Detection
S. Han, H. Song, S. Lee, S. Park, and M. Cha [British Machine Vision Conference, November 2021]
The Conflict Between People’s Urge to Punish AI and Legal Systems
G. Lima, M. Cha, C. Jeon, and K.S. Park [In Frontiers in Robots and AI, November 2021]
On the Social-Relational Moral Standing of AI: An Empirical Study Using AI-Generated Art
G. Lima, A. Zhunis, L. Manovich, and M. Cha [In Frontiers in Robots and AI, August 2021]
Analyzing Biases in Perception of Truth in NewsStories and Their Implications for Fact Checking
M. Babaei, A. Chakraborty, J. Kulshrestha, E.M. Redmiles, M. Cha, and K. Gummadi [In IEEE Transactions on Computational Social Systems, Accepted for publication, July 2021. (SCIE, IF=5.36)]
Finding Epic Moments in Live Content through Learning from Collective Decisions
H. Song, K. Park and M. Cha [In EPJ Data Science, Accepted for publication, 2021]
COVID-19 Vaccine Acceptance in the US and UK in the Early Phase of the Pandemic: AI-Generated Vaccines Hesitancy for Minors, and the Role of Governments
G. Lima, M. Cha, C. Cha, and H. Hwang [In Journal of the Korean Data Analysis Socie, 23(3), 1045–1064, June 2021] [PDF]
Urban green space and happiness in developed countries
O.-H. Kwon, I. Hong, J. Yang, D.Y. Wohn, W.-S. Jung, and M. Cha [In EPJ Data Science, 2021]
— Related News
Urban green space affects citizens’ happiness
Science Daily
Urban green space brings happiness when money can’t buy it anymore
Phys.org
Disruption in Chinese E-Commerce During COVID-19
Y. Yuan, M. Guan, Z. Zhou, S. Kim, M. Cha, D. Jin, and Y. Li [In Frontiers in Computer Science, 2021]
Prevalence of Misinformation and Factchecks on the COVID-19 Pandemic in 35 Countries: Observational Infodemiology Study
M. Cha, C. Cha, K. Singh, G. Lima, Y.-Y. Ahn, J. Kulshrestha, and O. Varol [In JMIR Human Factors, 8(1), January 2021]
The Medium and the Backlash: The Disparagement of the MeToo Movement in Online Public Discourse in South Korea
S.Y. Bae, T. Kim, Yu-i Ha, and M. Cha [In International Journal of Communication, 15, 768–791, January 2021. (IF=1.28)]
COVID-19 Discourse on Twitter in Four Asian Countries: Case Study of Risk Communication
S. Park, S. Han, J. Kim, M. M. Molaie, H. D. Vu, K. Singh, J. Han, W. Lee, and M. Cha [In Journal of Medical Internet Research (JMIR), 2021. doi:10.2196/23272. Impact Factor = 5.03 [SCIE]]
An Experimental Study to Understand User Experience and Perception Bias Occurred by Fact-checking Messages
S. Park, J. Y. Park, H. Chin, J. Kang, and M. Cha [In proc. of the Web Conference (WWW), April 2021. Acceptance rate for full paper = 20.6%] [PDF]
Improving Unsupervised Image Clustering With Robust Learning
S. Park, S. Han, S. Kim, D. Kim, S. Park, S. Hong, and M. Cha [In proc. of the 2021 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021] [Github]
The Presence of Unexpected Biases in Online Fact-checking
S. Park, J.Y. Park, J.-H. Kang, and M. Cha [In Harvard Kennedy School (HKS) Misinformation Review, 2020]
Learning to Detect Incongruence in News Headline and Body Text via a Graph Neural Network
S. Yoon, K. Park, M. Lee, T. Kim, M. Cha, and K. Jung [IEEE Access, To appear in 2021. (SCIE, IF=3.764)]
Automatically Detecting Image-Text Mismatch on Instagram with Deep Learning
Y. Ha, K. Park, S.J. Kim, J. Joo, and M. Cha [In Journal of Advertising, January 2021. (SSCI, IF=6.302)]
Human Perceptions on Moral Responsibility of AI: A Case Study in AI-Assisted Bail Decision-Making
G. Lima, N. G.-H., and M. Cha [In proc. of the ACM CHI Conference on Human Factors in Computing Systems, 2021]
Designing a Mobile Intervention Platform to Help Alleviate Insomnia Symptoms in College Students (대학생의 불면 증상 완화를 위한 모바일 중재 플랫폼 개발 연구)
박성규, 이상원, 안동현, 차미영 [Journal of the Korean Society of Biological Therapies in Psychiatry, Vol 27, No 1, 2021] [PDF]
Neural Embedding of Sneaker Designs over 23 Years
박성규, 송현호, 한성원, Lev Manovich, Emanuele Arielli, and 차미영 [한국정보과학회 KCC, June 2021]
쇼핑몰 상품 카테고리 분류를 위한 Hyperbolic Interaction Model의 적용과 분석
김시현, 이은지, 박성원, 김선동, 차미영 [한국정보과학회 KCC, June 2021]
뉴스 요약문을 기반으로 한 가짜 뉴스 탐지
J. Bian, S. Lee, K. Singh, and M. Cha [한국정보과학회 KCC, June 2021]
위키백과를 이용한 COVID-19 범유행 정보 구조 분석
김단우, 이다민, 명재현, 정창욱, 홍인호, Diego Sáez-Trumper, 윤진혁, 정우성, 차미영 [한국정보과학회 KCC, June 2021]
2020
A Comprehensive and Adversarial Approach to Unsupervised Embedding Learning
Y.-Z. Hsu, S. Han, S. Park, M. Cha, and C.-T. Li [In proc. of the IEEE International Conference on Big Data, 2020 (Acceptance Rate=15.5%)]
Anger contributes to the spread of COVID-19 misinformation
J. Han, M. Cha, and W. Lee [In Harvard Kennedy School (HKS) Misinformation Review, 2020]
Collecting the Public Perception of AI and Robot Rights
G. Lima, C. Kim, S. Ruy, C. Jeon, M. Cha [In proc. of the ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW), 2020]
Mitigating Embedding and Class Assignment Mismatch in Unsupervised Image Classification
S. Han, S. Park, S. Park, S. Kim, M. Cha [In proc. of the European Conference on Computer Vision (ECCV), August 2020]
Explaining the Punishment Gap of AI and Robots
K. Park, G. Lima, M. Cha, and C. Jeon [In proc. of the We Robot (International Conference on Law and Policy Relating to Robotics), August 2020]
From Anticipation to Action: Data Reveal Mobile Shopping Patterns During a Yearly Mega Sale Event in China
M. Guan, M. Cha, Y. Wang, J. Sun, and Y. Li., [Transactions on Knowledge and Data Engineering, June 2020. (SCI, IF=5.876)]
DATE: Dual Attentive Tree-aware Embedding for Customs Fraud Detection
S. Kim, Y.-C. Tsai, K. Singh, Y. Choi, E. Ibok, C.-T. Li, and M. Cha [In proc. of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020 (Acceptance Rate=16%)]
Learning to Score Economic Development from Satellite Imagery
S. Han, D. Ahn, S. Park, J. Yang, S. Lee, J. Kim, H. Yang, S. Park, and M. Cha [In proc. of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020 (Acceptance Rate=16%)]
Detecting Fake News in Social Media: An Asia-Pacific Perspective
M. Cha, W. Gao, and C.-T. Li [In Communications of the ACM (CACM) Big Trends, Vol 63, No 4, 68–71, 2020]
“Trust me, I have a Ph.D.”: A Propensity Score Analysis on the Halo Effect of Disclosing One’s Offline Social Status in Online Communities
K. Park, H. Kwak, H. Song, and M. Cha [In proc. of the International AAAI Conference on Weblogs and Social Media (ICWSM), 2020]
Lightweight and Robust Representation of Economic Scales from Satellite Imagery
S. Han, D. Ahn, H. Cha, J. Yang, S. Park, and M. Cha [In proc. of the AAAI Conference on Artificial Intelligence (AAAI), 2020]
Learning How Spectator Reactions Affect Popularity on Twitch
J. Kim, K. Park, H. Song, J.Y. Park, and M. Cha [In proc. of the IEEE Conference on Big Data and Smart Computing (BigComp), 2020]
Green Space and Happiness of Developed Countries
F. Hashemi, A. Behrouz, J. Yang, D.Y. Wohn, and M. Cha [In proc. of the IEEE Conference on Big Data and Smart Computing (BigComp), 2020. (Short Paper)]
Disruption in the Chinese E-Commerce During COVID-19
Y. Yuan, G. Muzhi, Z. Zhou, S. Kim, M. Cha, D. Jin, Y. Li [arXiv:2009.14605]
Carpe Diem, Seize the Samples Uncertain at the Moment for Adaptive Batch Selection
H. Song, M. Kim, S. Kim, J. Lee [In proc. of the ACM International Conference on Information and Knowledge Management (CIKM), 2020]
Ada-Boundary: Accelerating the DNN Training via Adaptive Boundary Batch Selection
H. Song, S. Kim, M. Kim, J. Lee [Machine Learning (SCI, IF=2.730, ECML-PKDD Journal track)]
Neural User Embedding From Browsing Events
M. An, S. Kim [In proc. of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2020]
Will Punishing Robots Become Imperative in the Future?
G. Lima, M. Cha, C. Jeon, and K. Park [In proc. of the Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems, 2020]
Responsible AI and Its Stakeholders
G. Lima, and M. Cha [In Fair & Responsible AI Workshop, co-located with the 2020 CHI Conference on Human Factors in Computing Systems, 2020]
Revisit Prediction by Deep Survival Analysis
S. Kim, H. Song, S. Kim, B. Kim, J. Lee [In proc. of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2020, Singapore]
BaitWatcher: A lightweight web interface for the detection of incongruent news headlines
K. Park, T. Kim, S. Yoon, M. Cha, and K. Jung [In Fake News, Disinformation, and Misinformation in Social Media-Emerging Research Challenges and Opportunities. Springer, 2020]
QoS-Based Zero-Rating of Cellular Applications
Ramneek, P. Hosein, S. Pack, and K. Singh [In proc. of the International Conference on Information Networking (ICOIN), January 2020]
A Risk Communication Event Detection Model via Contrastive Learning
M. Shin, S. Han, S. Park, M. Cha [In proc. of the 3rd NLP4IF Workshop on NLP for Internet Freedom: Censorship, Disinformation, and Propaganda – COLING workshop, 2020]
Human-in-the-loop solution for scoring economic development from geospatial data
S. Park, D. Ahn, S. Han, E. Lee, D. Kim, J. Yang, S. Lee, S. Park, H. Yang, J. Kim, M. Cha [HAMLETS (Human And Machine in-the-Loop Evaluation and Learning Strategies) – NeurIPS workshop, 2020]
Teaching Machines to Measure Economic Activities from Satellite Images: Challenges and Solutions
D. Ahn, M. Cha, S. Han, J. Kim, S. Lee, S. Park, S. Park, H. Yang, J. Yang [Banca d’Italia and Federal Reserve Board Joint Conference on Nontraditional Data & Statistical Learning with Applications to Macroeconomics (BIFRBConf), 2020]
Descriptive AI Ethics: Collecting and Understanding the Public Opinion
G. Lima, and M. Cha [Ethics in Design Workshop, ACM CSCW 2020]
DPESS: Daytime Satellite Imagery-based Prediction of Demographic Attributes Using Embedding Spatial Statistics (DPESS: 임베딩 공간 통계를 이용한 주간 위성영상 기반의 인구 통계학적 속성 예측)
H. Cha, S. Han, D. Ahn, S. Park, and M. Cha [In Journal of KIISE, 742-747, August 2020]
2019
Clustering Insomnia Patterns by Data from Wearable Devices: Algorithm Development and Validation Study
S. Park, S.-W. Lee, S. Han, M. Cha [In JMIR mHealth and uHealth (JMU), Vol 7, No 12, December 2019, e14473 (SCI-E, IF=4.3)]
Predicting New Adopters via Socially-Aware Neural Graph Collaborative Filtering
Y.-C. Tsai, M. Guan, C.-T. Li, M. Cha, Y. Li, and Y. Wang [In International Conference on Computational Data and Social Networks (CSoNet), 2019]
Learning Sleep Quality from Daily Logs
S. Park, C-T. Li, S. Han, C. Hsu, S.W. Lee, and M. Cha [In proc. of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), August 4–8, 2019, Anchorage, AK, USA (Acceptance Rate=14%)]
Detecting Incongruity Between News Headline and Body Text via a Deep Hierarchical Encoder
S. Yoon, K. Park, J. Shin, H. Lim, S. Won, M. Cha, K. Jung [In proc. of the AAAI Conference on Artificial Intelligence (AAAI), 2019. (Acceptance Rate=16%)]
Understanding Facebook News Posts Comment Reading and Reacting Behavior through Political Extremism and Cultural Orientation
M.Y. Almoqbel, D.Y. Wohn, R.A. Hayes, M. Cha [In Elsevier Computers in Human Behavior Vol 100, 118-126, November 2019 (SCI-E, IF=4.306)]
Analyzing Biases in Perception of Truth in News Stories and their Implications for Fact Checking
M. Babaei, A. Chakraborty, J. Kulshrestha, E.M. Redmiles, M. Cha, and K. Gummadi [In proc. of the ACM Conference on Fairness, Accountability, and Transparency (FAT*), 2019]
Predicting Time-Bounded Purchases During a Mega Shopping Festival
M. Guan, M. Cha, Y. Li, Y. Wang, and J. Yu [In proc. of the IEEE International Conference on Big Data and Smart Computing (BigComp), 2019]
Image Super Resolution Techniques Applied on Satellite Imagery
C. Phentmunee, H. Doan Thi, H. Dieu Vu, D. Ahn, H.Cha, S. Han, and M. Cha [In International Workshop and Challenge on Real-World Recognition from Low-Quality Images and Videos, co-located with ICCV, 2019]
Predicting Urbanization from Daytime Satellite Imagery based on Descriptive Statistics
D. Ahn, S. Han, H.Cha and M. Cha [In Workshop on AI and the United Nation SDGs, co-located with IJCAI, 2019]
The Fallacy of Echo Chambers: Analyzing the Political Slants of User-Generated News Comments in Korean Media
J. Han, Y. Lee, J. Lee, and M. Cha [In proc. of the 5th Workshop on Noisy User-generated Text (W-NUT 2019), co-located with EMNLP, 2019]
DPESS: Daytime Satellite Imagery-based Prediction of Demographic Attributes Using Embedding Spatial Statistics (DPESS: 임베딩 공간 통계를 이용한 주간 위성영상 기반의 인구 통계학적 속성 예측)
차현지, 한성원, 안동현, 박성원, 차미영 [한국정보과학회 KCC, 2019]
Detection of hate speech with emoticons using Twitch tv online streaming chat data (트위치 온라인 스트리밍 채팅 데이터를 이용한 이모티콘이 포함된 혐오 표현 탐지)
최영일, 김재헌, 차미영, 원동희 [한국정보과학회 KCC, 2019]
Predicting Demographics from Satellite Imagery based on Convolutional Neural Network and Transfer Learning (위성사진과 CNN 기반 전이 학습을 통한 인구 통계 예측)
박성원, 안동현, 차현지, 한성원, 차미영 [한국정보과학회 KCC, 2019]
Deep learning based classification of the quotation types embedded in economic news headlines (딥러닝 기반 모델을 활용한 국내 경제뉴스 제목 내 인용 형태 분류 및 뉴스의 의견성 분석)
이영인, 김정욱, 한지영, 김태균, 하유이, 차미영 [한국정보과학회 KCC, 2019]
Highlight Prediction on Online Streaming Video (온라인 스트리밍 동영상 인기 구간 예측)
송현호, 김정민, 박건우, 차미영 [한국정보과학회 KCC, 2019]
Robots for Class President: Children’s Positions Toward AI Robot Rights (로봇을 반장으로: AI 로봇 권리에 대한 어린이의 입장 연구)
G. Lima, S. Park, and M. Cha [한국정보과학회 KCC, 2019]