Using Exponential Random Graph Models for Social Networks to Understand Meta-Communication in Digital Media

Zhou Nie ()
Additional contact information
Zhou Nie: Faculty of Modern Language and Communication, Universiti Putra Malaysia, Serdang 43400, Malaysia

Social Sciences, 2023, vol. 12, issue 4, 1-11

Abstract: In recent years; digital media has garnered widespread interest from various domains. Despite advancements in the technology of digital media for globalized communication; disparities persist in user interaction patterns across different regions. These differences can be attributed to the presence of a control system, known as meta-communication, which shapes the coding of information based on social relationships. Meta-communication is formed in various social contexts, resulting in varying communication patterns among different groups. However, empirical research on the social processes that form meta-communication in digital media is scarce due to the challenges in quantifying meta-communication. This study aims to introduce exponential random graph models as a potential tool for analyzing meta-communication in digital media and to provide a preliminary understanding of its formation. The use of such models could prove valuable for researchers seeking to study meta-communication in digital media.

Keywords: exponential random graph models for social networks; meta-communication; digital media; social process; stochastic models (search for similar items in EconPapers)
JEL-codes: A B N P Y80 Z00 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2076-0760/12/4/236/pdf (application/pdf)
https://www.mdpi.com/2076-0760/12/4/236/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jscscx:v:12:y:2023:i:4:p:236-:d:1124360

Access Statistics for this article

Social Sciences is currently edited by Ms. Yvonne Chu

More articles in Social Sciences from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().