November 24, 2024
Ebrahim Sahafizadeh

Ebrahim Sahafizadeh

Academic Rank: Assistant professor
Address: Persian Gulf University, Bushehr, Iran
Degree: Ph.D in Computer Engineering
Phone: 077
Faculty: Faculty of Intelligent Systems and Data Science

Research

Title A Model for Social Communication Network in Mobile Instant Messaging Systems
Type Article
Keywords
Group-based communication, mobile instant messaging (MIM), social network
Journal IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
DOI https://10.1109/TCSS.2019.2958968
Researchers Ebrahim Sahafizadeh (First researcher) , Behrouz Tork Ladani (Second researcher)

Abstract

Mobile instant messaging (MIM) systems have provided very convenient ways for communication and information exchange in recent years. Interesting features of these applications have made them important platforms for spreading information, idea, behavior, and rumor. In contrast to traditional social networks, communication in MIM applications is not necessarily based on friendship relations. In group-based communication and broadcasting in channels that are prominent features of MIM systems, users may send messages to and receive messages from people with whom do not already have friendly relations. This kind of communication leads to the creation of special network in which not only users and their contact lists but also groups and channels are involved. Existing complex network models are not sufficiently expressive to represent this kind of communication network. In this article, we introduce the concept of social communication network (SCN) to be able to consider special structural properties of communications in MIM systems and propose a model for representing and generating the SCN in MIM systems. The proposed model covers all social communications between users, groups, and channels and exhibits the statistics observed in real-world data. We also redefine some existing properties and introduce some new properties of the MIM network that earlier models of complex networks do not capture. To evaluate the proposed model, we conduct a number of simulation experiments on the model and compare the results with a real-world graph that we have extracted from Telegram. The results show that SCN derived by the model is highly compatible with the real-world graph. The proposed model provides a useful basis for analysis and evaluation of MIM network properties.