During the past few years, social science have applied more and more of trace data. Trace data is large scale data set of the actions of people, for example Twitter activity around particular hashtag.
HYBRA focuses on working with trace data from social media (Facebook, Twitter) and major Finnish newspapers and support
We believe that many computational tools have been developed with an analysis strategy in mind. This helps to make the user experience smooth and help researchers a lot to work with that given analysis strategy. However, researcher is often bounded by do that analysis strategy and their creativity is bounded by the tools.
If you have a hammer everything looks like a nail. We want to avoid this and unleash the researchers to innovate with digital methods.
This means that a set of helper functions to support the data collection, wrangling and basic visualization is what is needed. We created these common tasks as programming libraries. It means there's a learnign curve: to utilize HYBRA, Python is required.
We believe that tooled with power of Python (and R) and HYBRA, researchers can create novel research approaches. The HYBRA smootheness many of the trivial tasks so researchers can focus on most valued-add activites in the analysis.