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This study utilizes the Analytic Hierarchy Process (AHP) in the selection of an optimal niche or category of videos for maximizing view count. The main income from videos is derived from RPM, which is a set amount per thousand views. A set of criteria was determined from attributes in the dataset that logically contribute to either the videos’ SEO or trend/popularity. The criteria in question were also determined by commonalities across a vast number of video content platforms, which focus more on the essential attributes of a video. In order to perform pairwise comparison, weights were derived from coefficients generated using Linear Regression. Following the creation of the model, we identify the categories with the highest potential for gaining views. Based on the results, the study may be performed in another time frame to reflect the major shifts in public interest over time. Thus, the importance of its repeatability and degree of usability across datasets from different platforms is emphasized. Doi: 10.28991/HIJ-2022-03-01-07 Full Text: PDF

AHP Approach for Determining Category in Social Media Content Creation in Order to Maximize Revenue per Mille (RPM)