The selection of social networking sites using fuzzy analytical hierarchy process / Nor Nazuin Nazarail

• Main Author: Nazarail, Nor Nazuin
• Format: Student Project
• Language: English
• Published: 2021
• Subjects: Online social networks; Fuzzy logic
• Online Access: http://ir.uitm.edu.my/id/eprint/44380/1/44380.pdf; http://ir.uitm.edu.my/id/eprint/44380/

Today online social networking platforms are expanding rapidly in use both personally and professionally. The adoption of digital channels is becoming more prominent around the world, with people of different cultures gradually accessing the internet to engage in networking sites. Nowadays, the rapid growth of social network use has made a magnificent channel for offering various services, increasing the beneficiary of services and business. Social networks have penetrated all ages of internet users and become an important means of communication and entertainment, including in the student community. As the number of social networking sites grows, the selection of networking sites for university students, including Twitter, Facebook, Google+, Instagram and so on, is becoming increasingly critical for website operators and advertisers alike. This platform is becoming essential for business performance in dealing with modern generations to increase revenues and profits. Moreover, as the number of social networks increases, the user's tendency to make a choice is difficult. The market for social networking sites is highly competitive and changes in line with the trend. The objective of the research is to rank the most popular social networking sites among users whether Facebook, Instagram and Twitter. Therefore, this study proposes a solution by developing a mathematical technique which is Fuzzy Analytical Hierarchy Process (F-AHP) to estimate the relative importance of site criteria used in deciding the social site. The result of this study shows that the Instagram as the first ranking with Functionality as the preferred criteria chosen and Revenue-generating opportunities as the sub-criteria with the highest normalized value.