headshot of Joseph Yun

Joseph Yun

Program Leader: Level 4 Information Technology
Research Professor
Misinformation Research Lab Electrical and Computer Engineering


Joseph T. Yun is the artificial intelligence and innovation architect for the University of Pittsburgh. He also is a research professor of electrical and computer engineering in the Swanson School of Engineering, University of Pittsburgh. Yun’s research is primarily focused on novel data science algorithms, user-centric analytics systems, computational advertising, novel technologies such as blockchain, and societal considerations of AI-based advertising and marketing (e.g., privacy, ethics). One specific focus area of Yun's current research is in the realm of misinformation and disinformation and the technologies that support its distribution. Yun is the principal investigator of the Social Media Macroscope, which is an open research environment for social media analytics (socialmediamacroscope.org). He is also an affiliate of Pitt Cyber and the Collaboratory Against Hate.


PhD in Informatics, University of Illinois at Urbana Champaign, 2018

MS in Advertising, University of Illinois at Urbana Champaign, 2014

BS in Computer Science, University of Illinois at Urbana Champaign, 2001

Yun, J.T., & Strycharz, J. (2023). Building the Future of Digital Advertising One Block at a Time: How Blockchain Technology Can Change Advertising Practice and Research. Journal of Current Issues & Research in Advertising, 44(1), 24-37.Informa UK Limited. doi: 10.1080/10641734.2022.2090464.

Donelson, C., Sutter, C., Pham, G.V., Narang, K., Wang, C., & Yun, J.T. (2021). Using a Machine Learning Methodology to Analyze Reddit Posts regarding Child Feeding Information. Journal of Child and Family Studies, 30(5), 1290-1298.Springer Science and Business Media LLC. doi: 10.1007/s10826-021-01923-5.

Pamuksuz, U., Yun, J.T., & Humphreys, A. (2021). A Brand-New Look at You: Predicting Brand Personality in Social Media Networks with Machine Learning. Journal of Interactive Marketing, 56, 55-69.SAGE Publications. doi: 10.1016/j.intmar.2021.05.001.

Sutter, C., Pham, G.V., Yun, J.T., Narang, K., Sundaram, H., & Fiese, B.H. (2021). Food parenting topics in social media posts: Development of a coding system, examination of frequency of food parenting concepts, and comparison across Reddit and Facebook. Appetite, 161, 105137.Elsevier BV. doi: 10.1016/j.appet.2021.105137.

Yun, J.T., Duff, B.R.L., Vargas, P.T., Sundaram, H., & Himelboim, I. (2020). Computationally Analyzing Social Media Text for Topics: A Primer for Advertising Researchers. Journal of Interactive Advertising, 20(1), 47-59.Informa UK Limited. doi: 10.1080/15252019.2019.1700851.

Yun, J.T., Segijn, C.M., Pearson, S., Malthouse, E.C., Konstan, J.A., & Shankar, V. (2020). Challenges and Future Directions of Computational Advertising Measurement Systems. JOURNAL OF ADVERTISING, 49(4), 446-458.Informa UK Limited. doi: 10.1080/00913367.2020.1795757.

Yun, J.T., Vance, N., Wang, C., Marini, L., Troy, J., Donelson, C., Chin, C.L., & Henderson, M.D. (2020). The Social Media Macroscope: A science gateway for research using social media data. FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 111, 819-828.Elsevier BV. doi: 10.1016/j.future.2019.10.029.

Yun, J.T., Duff, B.R.L., Vargas, P., Himelboim, I., & Sundaram, H. (2019). Can we find the right balance in cause-related marketing? Analyzing the boundaries of balance theory in evaluating brand-cause partnerships. PSYCHOLOGY & MARKETING, 36(11), 989-1002.Wiley. doi: 10.1002/mar.21250.

Yun, J.T., Pamuksuz, U., & Duff, B.R.L. (2019). Are we who we follow? Computationally analyzing human personality and brand following on Twitter. INTERNATIONAL JOURNAL OF ADVERTISING, 38(5), 776-795.Informa UK Limited. doi: 10.1080/02650487.2019.1575106.

Yun, J.T., & Duff, B.R.L. (2017). Is utilizing themes an effective scheme? Choice overload and categorization effects within an extensive online choice environment. COMPUTERS IN HUMAN BEHAVIOR, 74, 205-214.Elsevier BV. doi: 10.1016/j.chb.2017.04.038.

Wang, C., Marini, L., Chin, C.L., Vance, N., Donelson, C., Meunier, P., & Yun, J.T. (2019). Social Media Intelligence and Learning Environment: an Open Source Framework for Social Media Data Collection, Analysis and Curation. In 2019 15th International Conference on eScience (eScience).IEEE. doi: 10.1109/escience.2019.00035.