A Comment-Based Algorithm for Post-Ranking Rapprochement on Facebook

Mahdi Jemmali, Yousef Qawqzeh

Abstract


This work investigates the effects of a comment, in an individual post, voted by a reputed person. The proposed algorithm utilized 10 variables for ranking comment's owner represented by the value of \(\textit{Cor}\) variable. Then the model will analyze how such a vote will affect the rank of that post by increasing the upvotes or by increasing the downvotes. Eight variables are proposed to evaluate the rank of the post represented by the value of \(GW_p\) variable. At the end, the overall score of the post will be calculated represented by \(GS_p\) variable. Being simple and easy to implement, the proposed method is expected to measure the post-sensitive influence on participants on that given post. However, introducing user's weight (ranking) as a new parameter for the evaluation of post's weight, could highly correct the whole evaluation of post's ranking. As commenters vary in their weights (rankings), posts can be upvoted or downvoted because of commenter's opinion and thought on the given post. This work is novel and aimed at introduce a new method for post ranking that can be utilized for different purposes in different disciplinarians.

Keywords


Post ranking; Commenter’s weight; Upvotes; Downvotes; Social media; Facebook

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References


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