Pu ZHANG (张谱)

I am currently pursuing a MPhil at the Hong Kong University of Science and Technology (Guangzhou). My supervisor at this master program is Prof. Corey Kewei XU. I also have a co-supervisor, Prof. Jing TANG. My main research interests are disaster-related online public opinion and the application of large language model agents in the field of disaster risk perception.

I obtained a Bachelor of Administration degree (Regional Development in Rural Areas) and a Bachelor of Science degree (Data Science and Big Data Technology) from China Agricultural University. At that time I focused on social media online opinion research. My supervisor Prof. Feng KONG is a scholar in the field of disaster and emergency management.

Research Interests

Social Media Research
Computational Social Science
Disaster Risk Perception
Large Language Model for Agent-Based Analysis

news

Jun 11, 2024	I’m qualified for IGSS2024 and get a scholarship, I will be a guest at Wuhan University from June 23rd to June 29th!
Jun 07, 2024	I referenced alshedivat/al-folio, which is beautifully crafted. This website gets a new look!
Apr 20, 2024	My first SCI paper was published online. This paper was officially published on March 24, 2024, in the journal IJDRR.
Sep 01, 2023	I’m now starting my master’s degree at the Hong Kong University of Science and Technology (Guangzhou).
Jun 30, 2023	I graduated from the China Agricultural University. I had a wonderful four years here. I earned both a Bachelor of Administration and a Bachelor of Science degree.

selected publications

Research on online public opinion in the investigation of the “7–20” extraordinary rainstorm and flooding disaster in Zhengzhou, China

Pu Zhang, Hao Zhang, and Feng Kong

International Journal of Disaster Risk Reduction, 2024

Abs Bib DOI PDF

Sorting out the changing characteristics of online public opinion triggered by a series of events in the investigation and assessment of major natural disasters is of great practical significance for optimizing the work of disaster investigation and assessment, governing the ecology of online public opinion, and enhancing the effect of comprehensive disaster reduction. In this paper, we collected relevant comments from several official media accounts, such as People’s Daily, and evaluated their emotional color using a sentiment analysis method based on the BERT fine-tuning model. Furthermore, keyword co-occurrence semantic network theme analysis is conducted for texts presenting negative emotional overtones to assess the changes in public opinion hotspots. The impact of the relevant online public opinion characteristics and the release of the disaster investigation report on them was assessed in the context of the investigation report itself. Based on sorting out the characteristics of online public opinion on several related topics, targeted public opinion governance initiatives and relevant suggestions for improving the disaster investigation system are proposed. This paper is of positive significance for studying disaster public opinion and improving the effectiveness of emergency management of rainstorms and flooding disasters.
@article{ZHANG2024104422, title = {Research on online public opinion in the investigation of the “7–20” extraordinary rainstorm and flooding disaster in Zhengzhou, China}, journal = {International Journal of Disaster Risk Reduction}, volume = {105}, pages = {104422}, year = {2024}, issn = {2212-4209}, dimensions = {true}, url = {https://www.sciencedirect.com/science/article/abs/pii/S2212420924001845}, doi = {10.1016/j.ijdrr.2024.104422}, author = {Zhang, Pu and Zhang, Hao and Kong, Feng}, keywords = {Rainstorm and flooding disaster, Disaster investigation report, Disaster opinion research, Integrated disaster mitigation, Natural language processing}, }