Exploring the attributes of influential users in social networks using association rule mining

Association rule mining discovers interesting patterns and meaningful connections between items or actions performed by users on social media platforms. These connections can provide valuable insights into user behavior, preferences, and interactions within the social media ecosystem. This study utilizes the association rule mining to identify Key attributes of influential individuals who can effectively influence others to actively participate in activities such as writing posts, answering questions, and sharing posted content on popular social news aggregation and discussion websites such as reddit.com. The research relies on user profiles and activity logs as data sources for analysis. The study’s findings include the observation that highly influential sharers often engage in regular content creation and sharing related to topics like entrepreneurship, personal development, and professional growth. Furthermore, it suggests that influential sharers are active during both business and prime times. In terms of specific dimensions of interest, it was found that women are more likely to be influenced by individuals who frequently write about personal growth. Similarly, the study highlights that teenagers have the most influence over their peers. Additionally, when considering the interplay of age and gender, it has been identified that adult males, especially, possess the ability to convince and influence other males. The insights gained from this study can prove valuable to marketers seeking to target specific individuals for effective social marketing campaigns.