Main idea & conclusion
Framework
- Discovery: The “uncovering of latent structures and patterns” (Chinnov et al., 2015)
- Tracking: This step involves decisions on the data source (e.g. Twitter, Facebook), approach, method and output. A detailed sub ivision of this step can be found in Stieglitz et al. (2014). In several studies the completeness of different Twitter sources was compared (Driscoll & Walker, 2014; Morstatter, Pfeffer, & Liu, 2014; Morstatter, Pfeffer, Liu, & Carley, 2013).
- Preparation: Beyond this, the original framework does not elaborate on the preparation steps necessary.
- Analysis: Depending on the purpose there are several methods available, including social network analysis and opinion mining.
Key factors in big data analysis: "four V's"
- Volume: the storage space required
- Velocity: the speed of data creation coupled with the advantage gained from analysing the data in real time
- Variety: the fact that data takes many different forms. It is often unstructured or its structure is specific to the data source, and
- Veracity: uncertainty especially with regard to data quality.