doi: 10.7763/IJET.2018.V10.1042
Behavioral Analysis of Iranian Users in a Mobile Social Network
A. Abbaspour
1
,
Masoud Asadpour
2
- 1 Mobile Telecommunication company of Iran (MCCI), Iran
- 2 School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran
Abstract
It’s been almost more than fifteen years that social networks have become significant part of our everyday life. Social networks being so mainstream and available, owes its availability to developments in some other fields. Mobile network developments have been very significant in recent years. Introducing technologies such as 3G or LTE have been a major reason for almost every mobile subscriber to use social networks services. That’s the world that on demand access is more important than ownership. There are many different mobile social network applications, which competing each other with new services and feature every other day. In order to survive this competition there can be some analysis that can be done. One of them is about the behavioral aspect of users’ activities, that we can use to extract a pattern of users’ activity in social network applications. These patterns can be used to analyze user acquisition or churn. In this paper we will be talking about the behaviors of Iranian users in a mobile social network. We gathered the data by a third party application for Instagram and we are going to use different methods of visualization, statistical methods and analysis to show different patterns in users behaviors
Keywords
- Mobile social networks
- data visualization
- social network analysis
- behavioral analysis
- churn
- users correlation
How to Cite
A. Abbaspour and Masoud Asadpour, "Behavioral Analysis of Iranian Users in a Mobile Social Network," International Journal of Engineering and Technology, vol. 10, no. 1, pp. 100-107, 2018. https://doi.org/ 10.7763/IJET.2018.V10.1042
Copyright & License
Copyright © 2018 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).