Surendrabikram Thapa
Datos Biográficos
| ID | 3924920 |
|---|---|
| NOMBRE | Surendrabikram Thapa |
| NOMBRES | Surendrabikram |
| APELLIDO | Thapa |
| FIRMA | THAPA S |
| AFILIACIONES | Virginia Tech |
| ORCID | 0000-0003-4119-8239 |
| VERIFICADO | Sí |
| TOTAL DE OBRAS | 5 |
| TOTAL DE CITAS | 1 |
| TOTAL COMO AUTOR | 5 |
| TOTAL COMO EDITOR | 0 |
| PRIMER AÑO DE PUBLICACIÓN | 2022 |
| AÑO MÁS RECIENTE DE PUBLICACIÓN | 2025 |
| ÍNDICE H | 1 |
Mask-Net
Social media users often use disease or symptom terms in ways other than describing their health conditions, which can lead to flawed conclusions in data-driven public health surveillance. The health mention classification (HMC) task aims to identify posts in which users use disease or symptom terms to discuss their health conditions instead of using them for other reasons. Existing methods rely on features extracted from external resources and a…
Analysis of Environmental Screening and Mapping Tools
Background: Environmental screening and mapping (ESM) tools can characterize the spatial distribution of environmental hazards and their effects, health status, and demographics of communities. For communities impacted by environmental injustices, ESM tools can play an important role in identifying areas facing cumulative impacts (CI). Methods: We identified 36 state and federal ESM tools to analyze. Map layers/indicators were organized by subcat…
Large language models (LLM) in computational social science
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…
Incorporating historical information by disentangling hidden representations for mental health surveillance on social media
Exploiting linguistic information from Nepali transcripts for early detection of Alzheimer's disease using natural language processing and machine learning techniques
Large language models (LLM) in computational social science
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…
Exploiting linguistic information from Nepali transcripts for early detection of Alzheimer's disease using natural language processing and machine learning techniques
Incorporating historical information by disentangling hidden representations for mental health surveillance on social media
Mask-Net
Social media users often use disease or symptom terms in ways other than describing their health conditions, which can lead to flawed conclusions in data-driven public health surveillance. The health mention classification (HMC) task aims to identify posts in which users use disease or symptom terms to discuss their health conditions instead of using them for other reasons. Existing methods rely on features extracted from external resources and a…
Analysis of Environmental Screening and Mapping Tools
Background: Environmental screening and mapping (ESM) tools can characterize the spatial distribution of environmental hazards and their effects, health status, and demographics of communities. For communities impacted by environmental injustices, ESM tools can play an important role in identifying areas facing cumulative impacts (CI). Methods: We identified 36 state and federal ESM tools to analyze. Map layers/indicators were organized by subcat…
Large language models (LLM) in computational social science
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 (4 obras) · Artificial Intelligence (3 obras) · Psychology (3 obras) · Data science (2 obras) · Disease (2 obras) · Medicine (2 obras) · Pathology (2 obras) · Census (1 obra) · Cognition (1 obra) · Cognitive science (1 obra)