So sánh phương pháp

	Mô hình Đồ thị Ngẫu nhiên Lũy thừa (ERGM / p*)	Phân tích mạng lưới văn bản
Lĩnh vực	Phân tích mạng lưới	Khai phá văn bản
Họ	Process / pipeline	Process / pipeline
Năm ra đời	1986 (foundational); modern ERGM framework 1996–2007	2011 (Paranyushkin); 2005 (Diesner & Carley)
Người khởi xướng	Frank & Strauss (1986); extended by Wasserman & Pattison (1996) and Robins et al. (2007)	Dmitry Paranyushkin; Jana Diesner & Kathleen M. Carley
Loại	Probabilistic generative network model	Text-mining network method
Công trình gốc	Robins, G., Pattison, P., Kalish, Y., & Lusher, D. (2007). An introduction to exponential random graph (p*) models for social networks. Social Networks, 29(2), 173-191.	Paranyushkin, D. (2011). Identifying the Pathways for Meaning Circulation Using Text Network Analysis. Nodus Labs.
Tên gọi khác	ERGM, p-star model, p* model, Üstel Rastgele Graf Modeli (ERGM / p*)	semantic network analysis, word co-occurrence network, Metin Ağ Analizi (Text Network Analysis)
Liên quan	6	4
Tóm tắt	The Exponential Random Graph Model (ERGM), also known as the p* model, is a statistical framework for network analysis that models the probability of an observed network as a function of its local structural features — such as reciprocity, triangles, and degree distribution. Developed from the foundational work of Frank and Strauss (1986) and extended into the modern framework by Wasserman and Pattison (1996) and Robins et al. (2007), ERGM is the inferential standard for social network analysis, capable of testing whether observed network structures arise by chance or reflect genuine social processes.	Text network analysis models the words or concepts in a text as nodes and their co-occurrences as edges, then uses network metrics to reveal the structure of meaning. The approach was advanced by Diesner and Carley (2005) for communication networks and by Paranyushkin (2011) for tracing the pathways of meaning circulation in text.