Abstract:

he current breakthrough in internet 2.0 technology opens up the possibility of connecting individuals all over the globe via society 2.0 and web 2.0 technologies. This new age enables consumers to communicate directly with other people, businesses, and the government. People are willing to share their thoughts, points of view, and ideas on any issue in a variety of media. This opens up the possibility of making "Big Social Data" useful by integrating machine learning methodologies and social data analytics. To acquire a broad perspective on social media big data analytics, this research provides an overview of current studies in social media, data science, and machine learning. We show why social media data are important components of a better datadriven decision-making process. By integrating 5 V's and 10 Bigs, we propose and create the "Sunflower Model of Big Data" to describe big data and bring it up to speed with technology. We identify the top 10 social data analytics for use on social media sites. This paper discusses a thorough list of applicable statistical/machine learning approaches for implementing each of these big data analytics. To date, "Text Analytics" is the most often utilised analytics in social data analysis. To address the demand and give a clear understanding, we develop a taxonomy on social media analytics. This research paper includes discusses tools, approaches, and supporting data types. As a consequence, researchers will have an easier time determining which social data analytics would best meet their requirements

Description:

big data, social media, big data analytics, social media analytics