Big Data Analytics on Social Media

Reshma Gandale

Abstract: The rise of social media platforms like Twitter, Instagram, and Facebook has caused explosive growth of data appertained to as" big data. This data contains useful information about how druggies bear, what they suppose, and the trends that are arising. In this study, we explore how Big Data Analytics ways can be applied to use and dissect social media data to produce useful, practicable information. The study uses a quantitative system to dissect Data attained from intimately available sources through APIs and datasets. To ameliorate the quality of the data, preprocessing ways similar as data cleaning, filtering, and metamorphosis will be applied. Advanced Statistical ways, similar as machine literacy and Natural Language Processing NLP, will be used to perform sentiment analysis, textbook bracket, and trend discovery. To reuse, dissect, and store large quantities of data, distributed calculating fabrics e.g., Apache Hadoop and Apache Spark will be employed.

Keywords: Big Data, Social media, Instagram, Twitter, Facebook, Big Data Analytics, API, NLP, Apache Hadoop, Apache Spark