Association Rule Analysis-Based Identification of Influential Users in爐he燬ocial Media

The exchange of information is an innate and natural process that assist in content dispersal. Social networking sites emerge to enrich their users by providing the facility for sharing social interaction. extensive adoption also resulted user generation. There are diverse research areas explored researchers investigate influence media on confirmed have a significant impact markets, politics life. Facebook extensively used platform share information, thoughts opinions through posts comments. identification influential web has grown as hot field because vast applications instance political campaigns marketing, e-commerce, commercial and, etc. Prior studies either uses linguistic or graph-based representation network detection users. In this article, we incorporate association rule mining algorithms identify top frequent patterns. rules been computed using standard evaluation measures such support, confidence, lift, conviction. To verify results, involve conventional metrics example accuracy, precision, recall F1-measure according perspective. detailed experiments carried out benchmark College-Msg dataset extracted Facebook. obtained results validate quality visibility proposed approach. outcome propose model able generate temporal who consistent regular basis. preparation set help create knowledge-based systems which efficient widely recent era decision making solve real-world problems.