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bazdar, G., Abdollahi Azgomi, M. (2024). a computational model to evaluate the agent of influence operations in online social networks. Electronic and Cyber Defense, 12(1), 89-107.
gholamreza bazdar; Mohammad Abdollahi Azgomi. "a computational model to evaluate the agent of influence operations in online social networks". Electronic and Cyber Defense, 12, 1, 2024, 89-107.
bazdar, G., Abdollahi Azgomi, M. (2024). 'a computational model to evaluate the agent of influence operations in online social networks', Electronic and Cyber Defense, 12(1), pp. 89-107.
bazdar, G., Abdollahi Azgomi, M. a computational model to evaluate the agent of influence operations in online social networks. Electronic and Cyber Defense, 2024; 12(1): 89-107.

a computational model to evaluate the agent of influence operations in online social networks

پدافند الکترونیکی و سایبری
Article 8, Volume 12, Issue 1 - Serial Number 45, June 2024, Pages 89-107    PDF (1.06 M)
Document Type: Original Article
Authors
gholamreza bazdar1; Mohammad Abdollahi Azgomi* 2
1PhD student, Imam Hossein University (AS), Tehran, Iran
2Professor, University of Science and Technology, Tehran, Iran
Receive Date: 31 January 2024,  Revise Date: 19 April 2024,  Accept Date: 03 May 2024 
Abstract
The rapid and increasing use of online social networks among the society has provided a suitable field for the running cognitive and social influence operations. Optimal planning and implementation of influence operations depends on having a suitable framework for evaluating these operations. Evaluation of effective agents and actors in influence operations is one of the main requirements for evaluation of influence operations. On the other hand, considering the dynamics of online social networks and the ever-increasing production of mass data in it, it is necessary to use a computational approach to evaluate influence operations. Therefore, the purpose of this research is to find a computational model to evaluate the agents of influence operations in online social networks. In general, the methods of evaluating agent influence can be divided into three categories: qualitative evaluation, quantitative evaluation, and computational evaluation. Computational evaluation methods can be divided into two categories: methods based on machine learning (or deep learning) and methods based on hand-crafted features. The first category methods have higher accuracy but require a large amount of training data. Meanwhile, in issues such as ranking influence of agents, the preparation of labeled data is more complicated. Another disadvantage of methods based on machine learning is the inability to interpret the results. On the other hand, by using the theoretical structures related to influence in social networks, it is possible to achieve effective components in the calculation of influence. Meanwhile, better results can be achieved by combining theoretical and computational approaches. Therefore, in this article, we have presented a method that calculates the influence of agents by considering the network indicators and measures of agents' activity, by presenting the concept of user network power. In the proposed method, firstly, a model to evaluate the agent according to the important features for evaluating the influence operation is introduced based on the concept of network power, and then it is evaluated with the appropriate data set. According to the indicators used in this model, there is no data set that includes all these indicators, also we produced 3 data sets containing the desired indicators. The obtained results indicate that the presented model, in addition to interpretability and no need for training data, has a performance comparable to previous methods.
Keywords
Online social networks; influence operation evaluation; influence operation agents evaluation
Main Subjects
Modeling and simulation of electronic and cyber defense
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