Big data analytics of social media behavior for enhancing customer engagement

Social media services help people connect and communicate worldwide for sharing content, photos, videos and for following their friends. Globally, there is a huge amount of data generated every minute by users on social media platforms. Social Network Analysis (SNA) mainly uses big data analysis techniques and frameworks. Its goal is to extract meaningful insights from social media data in order to help individuals and organizations make the best decisions possible in a variety of areas, including business, marketing, politics, and health. With the daily growth of social media usage, social data analysis is drawing a lot of interest. The objective of such analysis is to find, understand and describe usage patterns to predict user behavior. Such analysis can help organizations and institutions understand the behavior of users to target products and services more effectively. For this goal, it’s vital to gather information about clients from social media, browser history, desktop and mobile applications, and other sources. This paper explores how big data analytics connects social media and discusses recent advances and enhancements in analyzing social networks. Marketers, organizations, and managers who are interested in observing the trends and gaining insights from social media data, will benefit from this study for making customer engagement decisions.