Social data

So far in this course, you have learned how to use largely tabular data, usually in the form of a Comma-Separated File (CSV). However, not all data comes in the form of a simple downloadable CSV file neatly arranged in columns and rows.

At some point in your data science journey, you might be exposed to another type of more structured data format, specifically JSON. In the next few steps, you will learn how to transform, use, and visualise information based on social media data, which commonly comes in JSON format.

Social media platforms generate a vast amount of data on a daily basis, on a variety of topics, which make it a key source of information for anyone interested in quantifying various aspects of our society.

In recent years, there has been an increased amount of research into social media data across a wide variety of disciplines, including sociology, computer science, marketing, and political science thanks to the availability of APIs for developers to extract data from individuals participating on social media platforms such as Twitter, Reddit, and Facebook. Alongside the ubiquity of social data, we have seen in the news that making personal social data commercially available may lead to some misuse.

Twitter is one of the main social media platforms used to promote views and opinions of people and communities on a wide variety of topics. One particular strand on which there is a large amount of traffic within Twitter is politics, where views are expressed on political parties and on news events that take place. Often these days, it is quite common that the news starts on Twitter rather than outside it. For these reasons Twitter data has become a good source of data for studying and evaluating attitudes towards individuals, products and brands, as well as political parties.