Applying fuzzy logic for multicriteria performance analysis of social media networking Online publication date: Mon, 25-Jul-2022
by Ridhima Mehta
International Journal of Fuzzy Computation and Modelling (IJFCM), Vol. 4, No. 1, 2022
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.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Fuzzy Computation and Modelling (IJFCM):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook