Advanced network modeling of complex social systems

This project is a Cooperative Research Project between the Center for Collaborative Research and Learning (C-COR & L), Irkutsk National, Russia and Center for Complex Networks & Social DataScience (CCNSD), Shahid Beheshti University, Tehran – Iran

Link to our partner’s website:

Team Members

Prof. Trufanov Andrey Ivanovich

Research Area: Social media, Information Technology, Computer Systems, and Artificial Intelligence

Innovation: The innovation states a Novel General Network platform for a description of pertinent entities and processes in social communities and social media through thorough ontologies, approaches, models, algorithms and applied instruments based on data got from principal online services.

Project Description:

“Social media has begun to reform the face of human life. We need to understand how our new societies work.”

For further clarification of the project domain one should note that two entities are defined as Social Networks:

I. Network as a set of social actors and their connections (a community of social actors);

II. Network as a Social media, a new medium for social interaction, based on social networking service.

A social network is a set of people or groups of people having interaction among them and Online Social Network (OSN) applications are Facebook, VK, MySpace, LinkedIn, Flicker, Twitter, YouTube, etc. Social networks topic has attracted social scholars since the beginning of the 20th century. Moreover, the impact of social networks has been a subject of investigation as complex networks from civil and military points of view. Several works were devoted to studying social networks for a better understanding of their dynamics and structural properties. A general network conception – Comprehensive Network Lace is just in line for separating entities and processes in the domain and describing human societies and social networking services both. Some studies went further and were concentrated on large-scale Social media, others took attention to the processes of community origin and growth. Studies based on real network societies supported by modern services have become increasingly valuable. 

Online social networks (OSN) make a modern environment which is also a complex networked system of humans. The role of online social networks and their impact on their users, from commercial, cultural, and political aspects, is of great importance. Therefore, it is important to study different aspects of online social networks and user engagement in this space in detail. We study the Farsi and Russian online social networks, with an emphasis on the Twitter network, to understand the unique features of this social media. We make use of big data available through the public APIs in our study to understand different events and interesting aspects of online social networks, focusing on the subspace occupied by Farsi and Russian speakers and their interactions. Given the rise of automation in online social networks, which, in addition to commercial uses, can be used for misinformation purposes, we pay special attention to social bots and their role in Farsi and Russian online social networks. To that end, we analyze social bots, cyborgs, and trolls, organized in troll farms. In particular, we are interested in studying the impact of the accounts that pretend to be regular human users, while, in fact, they are false accounts and intend to promote a commercial or political cause.

In parallel, but related efforts, we study other social networks. Nowadays lay people, medical organizations and professionals, governments have accented on counteracting COVID-19 which is crawling through over the globe. In this concern it is of sense to underline that infections are connected with social networks (SNs) (Klovdahl, 1985) and this connection has a triple nature:

–         – Physical contacts within SNs  supply the mechanism for infectious disease (ID) spread;

–         – Information in SNs accompanies the IDs and forms a key factor in counteracting the latter;

–         – Information spreads in an SN look similar to that infectious disease does.

Complex network and topology research has clarified the epidemic processes and proposed adequate models with the aim to support surveillance and infection control strategies and to enlighten the role of media.   

Studies in recent years paid significant attention to the issue of fake information spreading through online social media. The role of social robots has also been investigated. Moreover, researchers tried to clarify how emotions vary across individuals, evolve over time, and are connected to social ties. Networks have become a global international language for describing complex objects and processes in science, engineering, and human life. However, all the aforementioned works might be observed as a set of separated topics, even though they used a common instrument of complex networks.