{"doi":"10.1155/2021/6692210","title":"A Review of the Research Progress of Social Network Structure","abstract":"<jats:p>Social network theory is an important paradigm of social structure research, which has been widely used in various fields of research. This paper reviews the development process and the latest progress of social network theory research and analyzes the research application of social network. In order to reveal the deep social structure, this paper analyzes the structure of social networks from three levels: microlevel, mesolevel, and macrolevel and reveals the origin, development, perfection, and latest achievements of complex network models. The regular graph model, P1 model, P2 model, exponential random graph model, small‐world network model, and scale‐free network model are introduced. In the end, the research on the social network structure is reviewed, and social support network and social discussion network are introduced, which are two important contents of social network research. At present, the research on social networks has been widely used in coauthor networks, citation networks, mobile social networks, enterprise knowledge management, and individual happiness, but there are few research studies on multilevel structure, dynamic research, complex network research, whole network research, and discussion network research. This provides space for future research on social networks.</jats:p>","journal":"Complexity","year":2021,"id":46094,"datarank":1.5668771408807993,"base_score":3.970291913552122,"endowment":3.970291913552122,"self_citation_contribution":0.5955437870328184,"citation_network_contribution":0.971333353847981,"self_endowment_contribution":0.5955437870328184,"citer_contribution":0.971333353847981,"corpus_percentile":null,"corpus_rank":null,"citation_count":52,"citer_count":52,"citers_with_citation_signal":32,"citers_with_endowment":32,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":214273,"name":"Qian Huang","orcid":"0000-0002-9666-6741","position":1,"is_corresponding":false},{"id":214274,"name":"Xiaoyu Ge","orcid":"0000-0003-0977-1963","position":2,"is_corresponding":false},{"id":143368,"name":"Miao He","orcid":"0000-0002-9918-3729","position":3,"is_corresponding":false},{"id":214275,"name":"Shuqin Cui","orcid":"0000-0002-8476-5910","position":4,"is_corresponding":false},{"id":214276,"name":"Penglin Huang","orcid":"0000-0001-6985-845X","position":5,"is_corresponding":false},{"id":214277,"name":"Shuairan Li","orcid":"0000-0003-3303-1930","position":6,"is_corresponding":false},{"id":214278,"name":"Sai-Fu Fung","orcid":"0000-0002-3526-6568","position":7,"is_corresponding":false},{"id":36624,"name":"Ning Li","orcid":"0000-0002-6368-8194","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"base_score":3.970291913552122,"endowment":3.970291913552122,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"24551422","pmcid":null,"openalex_id":"https://openalex.org/W3118366610","authors":[],"funders":[{"funder_name":"National Natural Science Foundation of China","grant_id":"61440036","title":null},{"funder_name":"National Natural Science Foundation of China","grant_id":"61040029","title":null}],"total_grants":2,"fwci":4.8647,"citation_percentile":0.96014295,"influential_citations":4,"citation_trend":[{"year":2021,"count":2},{"year":2022,"count":12},{"year":2023,"count":12},{"year":2024,"count":12},{"year":2025,"count":10},{"year":2026,"count":4}],"oa_status":"gold","license":"cc-by","oa_locations":[{"url":"https://downloads.hindawi.com/journals/complexity/2021/6692210.pdf","host_type":"journal"},{"url":"https://downloads.hindawi.com/journals/complexity/2021/6692210.pdf","host_type":"GOLD"},{"url":"https://downloads.hindawi.com/journals/complexity/2021/6692210.pdf","host_type":"publisher"},{"url":"http://downloads.hindawi.com/journals/complexity/2021/6692210.pdf","host_type":"publisher"},{"url":"http://downloads.hindawi.com/journals/complexity/2021/6692210.xml","host_type":"publisher"},{"url":"https://onlinelibrary.wiley.com/doi/pdf/10.1155/2021/6692210","host_type":"publisher"},{"url":"https://doi.org/10.1155/2021/6692210","host_type":"journal"},{"url":"https://doaj.org/article/c16e3a8caa65415fb2ea7b9ba730efd0","host_type":"repository"},{"url":"https://hdl.handle.net/2031/cd0beeed-2c28-47c5-a3e4-f55a45248828","host_type":"repository"}],"fields_of_study":["Complex Network Analysis Techniques","Opinion Dynamics and Social Influence","Social Capital and Networks","Computer Science","Sociology"],"mesh_terms":[],"keywords":["Organizational network analysis","Social network (sociolinguistics)","Network science","Dynamic network analysis","Computer science","Network formation","Exponential random graph models","Complex network","Hierarchical network model","Social network analysis","Network model","Data science","Management science","Graph","Random graph","Artificial intelligence","Knowledge management","Theoretical computer science","Social media","World Wide Web","Computer network","Engineering"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-07-06T03:57:32.197019Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}