Decision Theory-based Content Selection and Ranking for Social Media Newsfeed using Fuzzy Analytic Hierarchy Process

News Feed for Social Media is the news stream that is constantly published in the middle of one’s home page. News Feed comprises status reports, photos, videos, interactions, app action, and reactions from people, blogs, and networks on social media that individuals follow. Determining the quality of limited content posts and ranking them to guide user interest is an important concept. This research focuses on prioritized the news feed post contents where the user’s recommended post will appear first in their news feed. Out of multiple input content, seven factors are categorized and Fuzzy AHP and AHP are applied here for ranking the factors where commented numbers get the highest-ranking and picture embedded post get the lowest ranking.