Mehwish Nasim
Biographic Data
| ID | 1753283 |
|---|---|
| NAME | Mehwish Nasim |
| GIVEN NAMES | Mehwish |
| FAMILY NAME | Nasim |
| SIGNATURE | NASIM M |
| AFFILIATIONS | The University of Western Australia |
| ORCID | 0000-0003-0683-9125 |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 2 |
| AUTHOR COUNT | 6 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2016 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
Large language models (LLM) in computational social science: Prospects, Current State, and Challenges
The advent of large language models (LLMs) has marked a new era in the transformation of computational social science (CSS). This paper dives into the role of LLMs in CSS, particularly exploring their potential to revolutionize data analysis and content generation and contribute to a broader understanding of social phenomena. We begin by discussing the applications of LLMs in various computational problems in social science including sentiment an…
Association of asthma exacerbations with paper mulberry (Broussenetia papyrifera) pollen in Islamabad: An observational study
Background: Although the role of airborne plant pollen in causing allergic rhinitis has been established, the association of concentrations of paper mulberry (Broussenetia papyrifera) pollens in the air and incidence of asthma exacerbations has not, despite an observed increase in the number of asthma patients attending physician clinics and hospital Accident and Emergency (A&E) Departments during the paper mulberry pollen season. We aimed to ass…
Incorporating historical information by disentangling hidden representations for mental health surveillance on social media
Promoting and countering misinformation during Australia's 2019-2020 bushfires: A Case Study of Polarisation
During Australia's unprecedented bushfires in 2019-2020, misinformation blaming arson surfaced on Twitter using . The extent to which bots and trolls were responsible for disseminating and amplifying this misinformation has received media scrutiny and academic research. Here, we study Twitter communities spreading this misinformation during the newsworthy event, and investigate the role of online communities using a natural experiment approach-be…
Exploring the effect of streamed social media data variations on social network analysis
Investigating Link Inference in Partially Observable Networks: Friendship Ties and Interaction
While privacy preserving mechanisms, such as hiding one's friends list, may be available to withhold personal information on online social networking sites, it is not obvious whether to which degree a user's social behavior renders such an attempt futile. In this paper, we study the impact of additional interaction information on the inference of links between nodes in partially covert networks. This investigation is based on the assumption that …
Large language models (LLM) in computational social science: Prospects, Current State, and Challenges
The advent of large language models (LLMs) has marked a new era in the transformation of computational social science (CSS). This paper dives into the role of LLMs in CSS, particularly exploring their potential to revolutionize data analysis and content generation and contribute to a broader understanding of social phenomena. We begin by discussing the applications of LLMs in various computational problems in social science including sentiment an…
Promoting and countering misinformation during Australia's 2019-2020 bushfires: A Case Study of Polarisation
During Australia's unprecedented bushfires in 2019-2020, misinformation blaming arson surfaced on Twitter using . The extent to which bots and trolls were responsible for disseminating and amplifying this misinformation has received media scrutiny and academic research. Here, we study Twitter communities spreading this misinformation during the newsworthy event, and investigate the role of online communities using a natural experiment approach-be…
Investigating Link Inference in Partially Observable Networks: Friendship Ties and Interaction
While privacy preserving mechanisms, such as hiding one's friends list, may be available to withhold personal information on online social networking sites, it is not obvious whether to which degree a user's social behavior renders such an attempt futile. In this paper, we study the impact of additional interaction information on the inference of links between nodes in partially covert networks. This investigation is based on the assumption that …
Exploring the effect of streamed social media data variations on social network analysis
Promoting and countering misinformation during Australia's 2019-2020 bushfires: A Case Study of Polarisation
During Australia's unprecedented bushfires in 2019-2020, misinformation blaming arson surfaced on Twitter using . The extent to which bots and trolls were responsible for disseminating and amplifying this misinformation has received media scrutiny and academic research. Here, we study Twitter communities spreading this misinformation during the newsworthy event, and investigate the role of online communities using a natural experiment approach-be…
Association of asthma exacerbations with paper mulberry (Broussenetia papyrifera) pollen in Islamabad: An observational study
Background: Although the role of airborne plant pollen in causing allergic rhinitis has been established, the association of concentrations of paper mulberry (Broussenetia papyrifera) pollens in the air and incidence of asthma exacerbations has not, despite an observed increase in the number of asthma patients attending physician clinics and hospital Accident and Emergency (A&E) Departments during the paper mulberry pollen season. We aimed to ass…
Incorporating historical information by disentangling hidden representations for mental health surveillance on social media
Large language models (LLM) in computational social science: Prospects, Current State, and Challenges
The advent of large language models (LLMs) has marked a new era in the transformation of computational social science (CSS). This paper dives into the role of LLMs in CSS, particularly exploring their potential to revolutionize data analysis and content generation and contribute to a broader understanding of social phenomena. We begin by discussing the applications of LLMs in various computational problems in social science including sentiment an…
Computer Science (5 works) · Social media (4 works) · Artificial Intelligence (3 works) · Data science (3 works) · Psychology (3 works) · World Wide Web (3 works) · Complex Network Analysis Techniques (2 works) · Data mining (2 works) · Opinion Dynamics and Social Influence (2 works) · Social Media and Politics (2 works)