Title: Applying fuzzy logic for multicriteria performance analysis of social media networking

Authors: Ridhima Mehta

Addresses: School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi, India

Abstract: Modelling the users' perception on network services and characteristics representing the efficiency of social media systems incorporates multiple attributes. In this paper, fuzzy logic theory is employed as a computationally intelligent technique for reviewing and assessing performance of the modern social networking sites with broader deployment. Implementation of the presented fuzzy methodology provides an overview of the accuracy and functionality evolving with the increasing size of social networks with massive data collection and their relationships to the customer behaviour. The proposed model based on the users' social characteristics can be used to evaluate the validity and utility enforcement on online social networks. We have used several error metrics comprising mean gamma deviance, R-squared and RMLSE for experimental verification of the proposed technique against the actual social networking data. Finally, accuracy of our fuzzy optimisation model is compared with the previous works in terms of acquiring considerably lower mean absolute error.

Keywords: fuzzy logic; membership function; reliability; social networks; utility.

DOI: 10.1504/IJFCM.2023.10048093

International Journal of Fuzzy Computation and Modelling, 2022 Vol.4 No.1, pp.51 - 72

Received: 17 Jul 2020
Accepted: 06 Jun 2021

Published online: 25 Jul 2022 *

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