Mengqi Zhan
Biographic Data
| ID | 6626238 |
|---|---|
| NAME | Mengqi Zhan |
| GIVEN NAMES | Mengqi |
| FAMILY NAME | Zhan |
| SIGNATURE | ZHAN M |
| AFFILIATIONS | The University of Texas at Arlington |
| ORCID | 0000-0003-2982-6482 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 6 |
| WORKS AS AUTHOR | 5 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2017 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
Automating Content Analysis With Multiple LLM Agents
Emerging research in computational social science has applied LLMs to automate content analysis, often by prompting a single model to act as a human coder. While a single LLM may suffice for a few manifest variables, it still falls short on diverse latent constructs. And the impact of LLM agent attributes on measurement outcomes remains unclear, limiting their validity for communication research. Drawing upon the literature on interacting agents …
Interplay of message features and source
There has been limited evidence regarding how disaster message features and source of social media communication independently and jointly affect users’ engagement behaviors. We conducted a content analysis of tweets collected from the Ariana Grande concert terrorist attack. Results from negative binomial regressions (N = 687) showed that the social support function of tweets affected reactive engagement, a higher level of content richness increa…
Reconciling Conflicting Results of Cultural Diversity’s Effect on Project Team Performance
Guided by the Categorization-Elaboration Model, we developed and tested a model to reconcile the conflicting results of cultural diversity’s influence on team performance. Previous theory and studies have inconsistent arguments and evidence regarding cultural diversity’s effects on team performance. We recognize that member cultural diversity is one possible influence on the variety and meanings of messages generated within groups, and the messag…
Innovating Teaching Practice Through Professional Learning Communities
The Professional Learning Community (PLC) model has been used to help faculty develop innovative teaching practices and diffuse effective strategies and resources throughout K-12 schools. Yet, whether and how PLCs influence research-focused higher education institutions remain unknown. Drawing on existing research on PLCs and the social network theory, this mixed-methods study investigated how participants shared what they learned during their ti…
Segmenting and Understanding Publics in a Social Media Information Sharing Network
This study segments social media publics and analyzes their informational behaviors during organizational crises. With a public-centric perspective, our study highlights how social media publics interact with each other (i.e., interdependence) and share different information through crisis stages (i.e., dynamics). Following the situational approach to segmentation, we identify different types of social media publics (i.e., influentials, broadcast…
Segmenting and Understanding Publics in a Social Media Information Sharing Network
This study segments social media publics and analyzes their informational behaviors during organizational crises. With a public-centric perspective, our study highlights how social media publics interact with each other (i.e., interdependence) and share different information through crisis stages (i.e., dynamics). Following the situational approach to segmentation, we identify different types of social media publics (i.e., influentials, broadcast…
Innovating Teaching Practice Through Professional Learning Communities
The Professional Learning Community (PLC) model has been used to help faculty develop innovative teaching practices and diffuse effective strategies and resources throughout K-12 schools. Yet, whether and how PLCs influence research-focused higher education institutions remain unknown. Drawing on existing research on PLCs and the social network theory, this mixed-methods study investigated how participants shared what they learned during their ti…
Segmenting and Understanding Publics in a Social Media Information Sharing Network
This study segments social media publics and analyzes their informational behaviors during organizational crises. With a public-centric perspective, our study highlights how social media publics interact with each other (i.e., interdependence) and share different information through crisis stages (i.e., dynamics). Following the situational approach to segmentation, we identify different types of social media publics (i.e., influentials, broadcast…
Interplay of message features and source
There has been limited evidence regarding how disaster message features and source of social media communication independently and jointly affect users’ engagement behaviors. We conducted a content analysis of tweets collected from the Ariana Grande concert terrorist attack. Results from negative binomial regressions (N = 687) showed that the social support function of tweets affected reactive engagement, a higher level of content richness increa…
Reconciling Conflicting Results of Cultural Diversity’s Effect on Project Team Performance
Guided by the Categorization-Elaboration Model, we developed and tested a model to reconcile the conflicting results of cultural diversity’s influence on team performance. Previous theory and studies have inconsistent arguments and evidence regarding cultural diversity’s effects on team performance. We recognize that member cultural diversity is one possible influence on the variety and meanings of messages generated within groups, and the messag…
Innovating Teaching Practice Through Professional Learning Communities
The Professional Learning Community (PLC) model has been used to help faculty develop innovative teaching practices and diffuse effective strategies and resources throughout K-12 schools. Yet, whether and how PLCs influence research-focused higher education institutions remain unknown. Drawing on existing research on PLCs and the social network theory, this mixed-methods study investigated how participants shared what they learned during their ti…
Automating Content Analysis With Multiple LLM Agents
Emerging research in computational social science has applied LLMs to automate content analysis, often by prompting a single model to act as a human coder. While a single LLM may suffice for a few manifest variables, it still falls short on diverse latent constructs. And the impact of LLM agent attributes on measurement outcomes remains unclear, limiting their validity for communication research. Drawing upon the literature on interacting agents …
Computer Science (4 works) · Psychology (4 works) · Political science (3 works) · Social Psychology (3 works) · Sociology (3 works) · Content analysis (2 works) · Knowledge management (2 works) · Misinformation and Its Impacts (2 works) · Public Relations and Crisis Communication (2 works) · Social media (2 works)