This study addresses the challenge of identifying influential users on social media platforms, particularly in the context of extremist ideologies that may threaten national security. Given the vast and growing volume of social media messages, manual analysis is impractical. The researchers developed a method to measure user influence by incorporating message content similarity and response immediacy into traditional link analysis techniques. Their experiments, conducted on a Dark Web forum dataset, demonstrated that integrating these weights significantly impacts the user influence ranking, especially when using the in-degree algorithm.