The expanding use of social networks has opened up a wealth of possibilities for practical applications, with influence analysis emerging as a crucial tool for understanding real-life dynamics. This study aims to offer a comprehensive survey of the state-of-the-art in influence analysis, focusing on strategies to address these challenges. The authors discuss various methods, including greedy algorithms, heuristics, and machine learning approaches, and also looks at how these algorithms are used in public health, marketing, and information sharing in the real world, giving a thorough review of how they might be used to effectively utilize the influence of social media. The main goal is to compare the advantages and disadvantages of the research methodologies and procedures used within these categories through a critical assessment. Additionally, the authors provide an in-depth overview of existing methods that address the key issue of privacy protection in influence maximization. This study also analyzes the latest applications where social influence is being used.