Publication Cover
AIDS Care
Psychological and Socio-medical Aspects of AIDS/HIV
Volume 35, 2023 - Issue 8
275
Views
4
CrossRef citations to date
0
Altmetric
Research Article

Reconstructing the social network of HIV key populations from locally observed information

ORCID Icon, ORCID Icon, ORCID Icon, , ORCID Icon & ORCID Icon
Pages 1243-1250 | Received 07 Jul 2020, Accepted 21 Jan 2021, Published online: 10 Feb 2021
 

ABSTRACT

Traditional surveys only provide local observations about the topological structure of isolated individuals. This study aims to develop a novel data-driven approach to reconstructing the social network of men who have sex with men (MSM) communities from locally observed information by surveys. A large social network consisting of 1075 users and their public relationships was obtained manually from BlueD.com. We followed the same survey-taking procedure to sample locally observed information and adapted an Exponential Random Graph Model (ERGM) to model the full structure of the BlueD social network (number of local nodes N = 1075, observed average degree k = 6.46). The parameters were learned and then used to reconstruct the MSM social networks by two real-world survey datasets in Hong Kong (N = 600, k = 5.61) and Guangzhou (N = 757, k = 5). Our method performed well on reconstructing the BlueD social network, with a high accuracy (90.3%). In conclusion, this study demonstrates the feasibility of using parameters learning methods to reconstruct the social networks of HIV key populations. The method has the potential to inform data-driven intervention programs that need global social network structures.

Acknowledgement

We would like to express our gratitude for all reviewers for their constructive comments and valuable suggestions. This study is funded in part by the National Natural Science Foundation of China (NSFC) Grant Nos. 71972164, 71672163 and 81903371 and in part by the Health and Medical Research Fund Grant (HMRF) No. 16171991.

Disclosure statement

No potential conflict of interest was reported by authors.

This article is part of the following collections:
Harnessing Big Data to End HIV

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 464.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.