دورية أكاديمية

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

التفاصيل البيبلوغرافية
العنوان: Using Exponential Random Graph Models for Social Networks to Understand Meta-Communication in Digital Media
المؤلفون: Zhou Nie
المصدر: Social Sciences, Vol 12, Iss 4, p 236 (2023)
بيانات النشر: MDPI AG, 2023.
سنة النشر: 2023
المجموعة: LCC:Social Sciences
مصطلحات موضوعية: exponential random graph models for social networks, meta-communication, digital media, social process, stochastic models, Social Sciences
الوصف: 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.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2076-0760
العلاقة: https://www.mdpi.com/2076-0760/12/4/236Test; https://doaj.org/toc/2076-0760Test
DOI: 10.3390/socsci12040236
الوصول الحر: https://doaj.org/article/06dd0819ac404ed594146adfead2bb7bTest
رقم الانضمام: edsdoj.06dd0819ac404ed594146adfead2bb7b
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20760760
DOI:10.3390/socsci12040236