Faculty Profile

Lingzi Hong

Title
Assistant Professor
Department
Information Science
College
College of Information

    

Education

PhD, University of Maryland, 2019.
Major: Information Studies

Current Scheduled Teaching*

INFO 5090.200, Practicum and Internship in the Field Study, Summer 2024
INFO 4900.702, Special Problems, Summer 2024
INFO 5091.200, Data Science Internship, Spring 2024 Syllabus
INFO 5709.004, Data Visualization and Communication, Spring 2024 Syllabus
INFO 6950.725, Doctoral Dissertation, Spring 2024
DTSC 3010.020, Introduction to Data Science, Spring 2024 Syllabus
INFO 5090.200, Practicum and Internship in the Field Study, Spring 2024 Syllabus
INFO 4900.002, Special Problems, Spring 2024
INFO 6900.028, Special Problems, Spring 2024

* Texas Education Code 51.974 (HB 2504) requires each institution of higher education to make available to the public, a syllabus for undergraduate lecture courses offered for credit by the institution.

Previous Scheduled Teaching*

INFO 5091.001, Data Science Internship, Fall 2023 Syllabus
INFO 6950.028, Doctoral Dissertation, Fall 2023
DTSC 3010.020, Introduction to Data Science, Fall 2023 Syllabus SPOT
INFO 5090.200, Practicum and Internship in the Field Study, Fall 2023 Syllabus SPOT
INFO 6900.028, Special Problems, Fall 2023
INFO 6950.701, Doctoral Dissertation, Summer 10W 2023
INFO 5090.200, Practicum and Internship in the Field Study, Summer 10W 2023 Syllabus SPOT
INFO 4900.702, Special Problems, Summer 10W 2023
INFO 5091.200, Data Science Internship, Spring 2023 Syllabus
INFO 5709.004, Data Visualization and Communication, Spring 2023 Syllabus SPOT
INFO 6950.725, Doctoral Dissertation, Spring 2023
INFO 3010.020, Introduction to Data Science, Spring 2023 Syllabus SPOT
INFO 5090.020, Practicum and Internship in the Field Study, Spring 2023 Syllabus SPOT
INFO 5090.200, Practicum and Internship in the Field Study, Spring 2023 Syllabus SPOT
INFO 4900.002, Special Problems, Spring 2023
INFO 6950.028, Doctoral Dissertation, Fall 2022
INFO 3010.020, Introduction to Data Science, Fall 2022 Syllabus SPOT
INFO 5090.200, Practicum and Internship in the Field Study, Fall 2022 Syllabus
INFO 5090.220, Practicum and Internship in the Field Study, Fall 2022 SPOT
INFO 6660.028, Readings in Information Science, Fall 2022
INFO 4900.002, Special Problems, Fall 8W2 2022
INFO 6900.028, Special Problems, Fall 2022
INFO 4907.001, Data Visualization, Summer 5W2 2022 Syllabus SPOT
INFO 5709.001, Data Visualization and Communication, Summer 5W2 2022 Syllabus SPOT
INFO 5709.600, Data Visualization and Communication, Summer 5W2 2022 Syllabus SPOT
INFO 5090.002, Practicum and Internship in the Field Study, Summer 10W 2022 Syllabus SPOT
INFO 4900.002, Special Problems, Summer 10W 2022
INFO 3010.002, Introduction to Data Science, Spring 2022 Syllabus SPOT
INFO 5090.002, Practicum and Internship in the Field Study, Spring 2022 Syllabus SPOT
INFO 5090.202, Practicum and Internship in the Field Study, Spring 2022 Syllabus SPOT
INFO 6660.009, Readings in Information Science, Spring 2022
INFO 4900.001, Special Problems, Spring 2022
INFO 6900.714, Special Problems, Spring 2022
INFO 5709.501, Data Visualization and Communication, Fall 2021 Syllabus SPOT
INFO 3010.002, Introduction to Data Science, Fall 2021 Syllabus SPOT
INFO 3010.003, Introduction to Data Science, Fall 2021 Syllabus SPOT
INFO 5090.001, Practicum and Internship in the Field Study, Fall 2021 Syllabus SPOT
INFO 6900.706, Special Problems, Fall 2021
INFO 5090.001, Practicum and Internship in the Field Study, Summer 5W2 2021
INFO 5090.002, Practicum and Internship in the Field Study, Summer 10W 2021 SPOT
INFO 4900.702, Special Problems, Summer 10W 2021
INFO 5709.002, Data Visualization and Communication, Spring 2021 Syllabus SPOT
INFO 5090.002, Practicum and Internship in the Field Study, Spring 2021 Syllabus SPOT
INFO 4900.751, Special Problems, Spring 2021 Syllabus
INFO 6910.703, Special Problems, Spring 2021
INFO 3010.002, Introduction to Data Science, Fall 2020 Syllabus SPOT
INFO 3010.003, Introduction to Data Science, Fall 2020 Syllabus SPOT
INFO 6900.705, Special Problems, Fall 2020
INFO 4907.001, Data Visualization, Summer 5W2 2020 Syllabus SPOT
INFO 5709.001, Data Visualization and Communication, Summer 5W2 2020 Syllabus SPOT
INFO 5709.005, Data Visualization and Communication, Summer 5W2 2020 SPOT
INFO 4907.001, Data Visualization, Spring 2020 Syllabus
INFO 3010.002, Introduction to Data Science, Spring 2020 Syllabus
INFO 6900.710, Special Problems, Spring 2020
INFO 3010.002, Introduction to Data Science, Fall 2019 Syllabus SPOT

* Texas Education Code 51.974 (HB 2504) requires each institution of higher education to make available to the public, a syllabus for undergraduate lecture courses offered for credit by the institution.

Published Publications

Published Intellectual Contributions

Abstracts and Proceedings
Velverthi, N. R., Prybutok, V., Hong, L. (2023). Investigating Factors Affecting Emerging Adults Usage of Patient Portals. iConference 2023. https://www.ideals.illinois.edu/items/126407
Kim, J., Hong, L., Evans, S. A., Ali, I., Rice-Oyler, E. (2023). Toward an understanding of data literacy needs in community colleges: A conceptual framework. ACRL 2023.
Hong, L., Yu,, Moen, W. E. (2020). Revealing the Disciplinary Landscape of Data Science Journals. ALISE.
Book Chapter
Kim, J., Davis, T., Hong, L. (2022). Augmented Intelligence: Enhancing Human Decision Making. Bridging Human Intelligence and Artificial Intelligence. 151-170. Springer. https://doi.org/10.1007/978-3-030-84729-6_10
Conference Proceeding
Yu, X., Zhao, A., Blanco, E., Hong, L. (2023). A Fine-Grained Taxonomy of Replies to Hate Speech. 7275-7289. Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing.
Mohotarema, R., Hong, L., Ryan, S. E. (2023). A brief survey of financial misinformation: Typologies, theories, and detection methods. Proceedings of the Multi-disciplinary Information Research Symposium at the University of North Texas.
Kim, J., Hong, L., Evans, S. A., Rice-Oyler, E., Ali, I. Development and Validation of a Data Literacy Assessment Scale. Proceedings of the Association for Information Science and Technology.
Dumas, C., Ghosh, S., Hong, L., Karami, A., Vaidya, P. (2023). Online Incivility and Contextual Factors: Data‐driven Detection and Analysis. 60(1), 770-774. Proceedings of the Association for Information Science and Technology.
Zeleke, M., Hong, L., Kaz-Onyeakazi, I., Smith, D. L., Milburn, S., Esener, Y. #NoMore: An Analysis of Topics and Sentiments Indicative of the War in Ethiopia. iSchools/ iConference 2023 Proceedings. https://hdl.handle.net/2142/117377
Gao, L., Hong, L., Mashhadi, A. (2022). Nostalgic Analysis of Location based Tweets. Glasgow: The 13th International Conference on Social Informatics. https://doi.org/10.1007/978-3-031-19097-1_27
Luo, P., Hong, L., Wang, J., Wang, S., Guo, X., Gao, Z., S. (2022). Learning Domain-specific Semantic Representation from Weakly Supervised Data to Improve Research Dataset Retrieval. Pittsburgh: 85th Annual Meeting of the Association for Information Science and Technology. https://doi.org/10.1002/pra2.616
Yu, X., Mashhadi, A., Boy, J., Nielsen, R. C., Hong, L. (2022). Causal Impact Model to Evaluate the Diffusion Effect of Social Media Campaigns. Coimbra: Proceedings of 20th European Conference on Computer-Supported Cooperative Work. https://dl.eusset.eu/handle/20.500.12015/4367
Yu, X., Xie, Z., Mashhadi, A., Hong, L. (2022). Multi-task Models for Multi-faceted Classification of Pandemic Information on Social Media. (978-1-4503-9191-7), 327-335. Barcelona: 14th ACM Web Science Conference 2022. https://dl.acm.org/doi/abs/10.1145/3501247.3531552
Yu, X., Blanco, E., Hong, L. Hate Speech and Counter Speech Detection: Context Does Matter. 2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics.
Yu, X., Boy, J., Nielsen, R., Hong, L. (2022). Linguistic Characteristics of Social Media Messages Spreading across Geographic and Linguistic Boundaries. ECSM 2022 9th European Conference on Social Media. https://www.academic-conferences.org/conferences/ecsm/
Hoang, N., Nie, D., Taivanbat, B., Liu, Y., Hong, L., Jason, T., Cheng, L. (2022). Eddie- Transformer: Enriched Disease Embedding Transformer for X-Ray Report Generation. Kolkata: 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI).
Xie, Z., Jayanth, A., Yadav, K., Ye, G., Hong, L. (2021). Multi-faceted Classification for the Identification of Informative Communications during Crises: Case of COVID-19. IEEE COMPSAC. https://ieeexplore.ieee.org/abstract/document/9529603
Yu, X., Reddy, D. S., Bentula, L., Hong, L. (2020). Characteristics of Information Spreading across Nations. Proceedings of the Association for Information Science and Technology.
Yu, X., Boy, J., Hong, L. (2020). The Effect of Structural Affinity on the Diffusion of a Transnational Online Movement: The Case of #MeToo. International Conference on Social Informatics.
Hong, L., Wu, J., Zou, Z. (2020). Spatial Accessibility and Equity of Public Libraries in Urban Settings. International Conference on Information. https://doi.org/10.1007/978-3-030-43687-2_45
Wu, J., Hong, L., Frias-Martinez, V. (2019). Predicting Perceived Level of Cycling Safety for Cycling Trips. Other. 456-459. Chicago, Illinois: 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2019).
Journal Article
Navya, V., Prybutok, V. R., Prybutok, G. L., Hong, L. (2023). Influence of risk factors on the adoption intentions of emerging adults towards patient portals. Decision Making and Analysis. 1(1), pp. 48-56.
Evans, S. A., Hong, L., Kim, J., Rice-Oyler, E., Ali, I. (2023). Community College Students’ Self-Assessment of Data Literacy: Exploring Differences Amongst Demographic, Academic, and Career Characteristics. Information and Learning Sciences. https://www.emerald.com/insight/content/doi/10.1108/ILS-06-2023-0065/full/html
Ryan, S. E., Hong, L., Rashid, M. (2023). From Corpus Creation to Formative Discovery: The Power of Big Data-Rhetoric Teams and Methods. Review of Communication. 23(1), . National Communication Association.
Aoyama, K., Hong, L., Flege, J., Yamada, R., Yamada, T. (2023). Relationships between acoustic characteristics and intelligibility scores: Japanese adults’ and children’s productions of American English liquids. Language and Speech. 66(4), . SageJournals.
Ye, G., Ze, P., Wei, J., Hong, L., Li, S., Wu, C. (2022). Dynamic sentiment sensing of cities with social media data. The Electronic Library. 40(4), 413-434. Emerald.
Ali, I., Hong, L., Chen, J. (2022). Remote Cataloging Productivity: An Exploratory Study in A National Library. Library Management. Emerald. https://doi.org/10.1108/LM-12-2021-0109
Kahanek, A., Yu,, Philbrick, J., Cleveland, A. D., Hong, L. (2021). Temporal Variations and Spatial Disparities in Public Sentiment Toward COVID-19 and Preventive Practices in the United States: Infodemiology Study of Tweets. JMIR Infodemiology. https://infodemiology.jmir.org/2021/1/e31671
Cheng, W., Xu,, Wu, J., Hong, L. (2021). Read with Me: Understanding Reading and Social Interaction Behavior through the Lens of Vlogging. Library Development.
Cheng, W., Wu, J., Moen, W. E., Hong, L. (2021). Assessing the Spatial Accessibility and Spatial Equity of Public Libraries’ Physical Locations. Library and Information Science Research. https://doi.org/10.1016/j.lisr.2021.101089
Hong, L., Frias-Martinez, V. (2020). Modeling and Predicting Evacuation Flows during Hurricane Irma. EPJ Data Science.
Hong, L., Moen, W. E., Yu, X., Chen, J. (2020). The Disciplinary Research Landscape of Data Science Reflected in Data Science Journals. Information Discovery and Delivery.
Poster
Kim, J., Hong, L., Evans, S. A. (2019). Defining Data Literacy: An Empirical Study of Data Literacy Dimensions. Association of Library and Information Science Education. https://hdl.handle.net/2142/110887

Awarded Grants

Contracts, Grants and Sponsored Research

Fellowship
Hong, L., "CLEAR Stipend," Sponsored by Center for Learning Experimentation, Application, & Research (CLEAR), University of North Texas, $500 Funded. (February 1, 20202020).
Hong, L., "Youth Scholar Seminar Travel Fund," Sponsored by Beijing Normal University, International, $2800 Funded. (December 6, 2019December 25, 2019).
Grant - Research
Hong, L., "Outcome-constrained Large Language Models for Counter Hate Speech," Sponsored by OpenAI, International, $20000 Funded. (December 2023 – Present).
Kim, J., Evans, S. (Co-Principal), Hong, L. (Co-Principal), "Students data literacy needs in community colleges: Perceptions of librarians, students and faculty," Sponsored by Institute of Museum and Library Services, Federal, $118996 Funded. (August 1, 2022July 31, 2024).
Hong, L. (Principal), "Counter Hate Speech Detection and Generation," Sponsored by University of North Texas, University of North Texas, $3000 Funded. (November 20212022).
Hong, L. (Principal), "Data-driven Methods to Detect Online Aggression," Sponsored by University of North Texas, University of North Texas, $2445 Funded. (May 26, 2021December 2021).
Evans, S. (Principal), Hong, L. (Co-Principal), "Comparative Study of Data Literacy Education for College Freshmen in US and China," Sponsored by University of North Texas, University of North Texas, $1500 Funded. (December 18, 20192020).
Hong, L., "Global Venture Fund - Hosting Visiting Scholar," Sponsored by University of North Texas, University of North Texas, $2000 Funded. (December 18, 20192020).
Hong, L. (Principal), "Data-driven Methods to Understand Social Media Participation and the Outcomes in Social Movements," Sponsored by College of Information, University of North Texas, $4943 Funded. (November 6, 2019August 2020).
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Overall
Summative Rating
Challenge and
Engagement Index
Response Rate

out of 5

out of 7
%
of
students responded
  • Overall Summative Rating (median):
    This rating represents the combined responses of students to the four global summative items and is presented to provide an overall index of the class’s quality. Overall summative statements include the following (response options include a Likert scale ranging from 5 = Excellent, 3 = Good, and 1= Very poor):
    • The course as a whole was
    • The course content was
    • The instructor’s contribution to the course was
    • The instructor’s effectiveness in teaching the subject matter was
  • Challenge and Engagement Index:
    This rating combines student responses to several SPOT items relating to how academically challenging students found the course to be and how engaged they were. Challenge and Engagement Index items include the following (response options include a Likert scale ranging from 7 = Much higher, 4 = Average, and 1 = Much lower):
    • Do you expect your grade in this course to be
    • The intellectual challenge presented was
    • The amount of effort you put into this course was
    • The amount of effort to succeed in this course was
    • Your involvement in course (doing assignments, attending classes, etc.) was
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