The avalanche of social network data is a result of communication platforms being developed for the last two decades. These are the platforms that evolved from chat rooms to personal information sharing and finally, social and professional networks. Among many, Facebook, Twitter, Instagram, Pinterest, and LinkedIn have emerged as the modern day social media. These platforms collectively have reach of more than a billion individuals across the world, sharing their activities and interaction with each other. Sharing of their data by these media through APIs and other technologies has given rise to a new field called social media analytics. This has multiple applications, such as in marketing, personalized recommendations, research, and societal. modern data science techniques such as machine learning and text mining are widely used for these applications. Python is one of the most programming languages used for these techniques. However, manipulating the unstructured-data from social networks requires a lot of precise processing and preparation before coming to the most interesting bits.
In the next chapter, we will see the way this data from social networks can be harnessed, processed, and prepared to make a sandbox for interesting analysis and applications in the subsequent chapters.
