Abstract : The recent advancement in internet 2.0 creates a scope to connect people worldwide using society 2.0 and web 2.0 technologies. This new era allows the consumer to directly connect with other individuals, business corporations, and the governmentPeople are open to sharing opinions, views, and ideas on any topic in different formats out loud. This creates the opportunity to make the “Big Social Data” handy by implementing machine learning approaches and social data analyticsThis study offers an overview of recent works in social media, data science, and machine learning to gain a wide perspective on social media big data analytics. We explain why social media data are significant elements of the improved data-driven decision-making process. We propose and build the “Sunflower Model of Big Data” to define big data and bring it up to date with technology by combining 5 V’s and 10 Bigs. We discover the top ten social data analytics to work in the domain of social media platforms. A comprehensive list of relevant statistical/machine learning methods to implement each of these big data analytics is discussed in this work. Text Analytics” is the most used analytics in social data analysis to date. We create a taxonomy on social media analytics to meet the need and provide a clear understandingTools, techniques, and supporting data type are also discussed in this research workAs a result, researchers will have an easier time deciding which social data analytics would best suit their needs..
 ? We propose and build the Sunflower Model of Big Data to define big data and bring it up to date with technology by combining 5 V’s and 10 Bigs. We discover the top ten social data analytics to work in the domain of social media platforms. ? This section investigates the concept of big data and proposes a new dynamic approach to defining big data. ? To reflect the combination of 5 V’s and 10 Bigs in big data, we develop and propose the “Sunflower Model of Big Data ? We propose this as a flexible and dynamic model.
 ? The series of tasks from the SMS is mostly used to collect and scrutinize scientific articles from a certain topic area to answer some predetermined questions. The strategy behind this is to find and assess all applicable articles to address specific problems ? Sequential activities by following a series of independent tasks lead to the ultimate goal in this system ? Adjustability and variety in big social data require data analytics, machine learning, and data science in the domain of social media data analysis.
 ? This work will review existing computational and digital pathology methods for breast cancer diagnosis with a special focus on deep learning. The paper starts by reviewing public datasets related to breast cancer diagnosis. Additionally, existing deep learning methods for breast cancer diagnosis are reviewed. The publicly available code repositories are introduced as well. The paper is closed by highlighting challenges and future works for deep learning-based diagnosis
 ? We use the advance search and filter option provided by each of these databases. ? Video analytics shows the recent advancement of technology in social data analysis ? social media, big data, and mental health Current advances and ethical implications ? Many disciplines and sectors have advanced as a result of the widespread use of social media data and big data analytics. There are numerous hurdles and limitations to working in this field.
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