Who are the most active MEPs in a certain issue?
who are the most active MEPs in a certain issue?
About this classification:
The classification works on the corpus of all the parliamentary questions (oral and written) presented during the VIII term.
The corpus is projected in a vector space where the dimensions are the keywords selected through a technique that involves the use of Markov Chains.
In this space, every text is represented by the TF-IDF (term frequency–inverse document frequency) vector.
On this vector space we've trained two different classifiers (svm and random forest). Combining the two classifiers we reach a precision of 81% on our test set.
As you may understand, classifying parliamentary texts involves knowledge of the domain, care when combining the classifiers and a high quality training. Even when all these elements are there, this semi-automatic classification can hardly be perfect, but it's good to continously try to improve it.
Every feedback and help is then more than welcome!
Select a general topic to see who are the most active MEPs. We categorize written and oral questions applying our algorithms and the EU Policy Agendas codebook.
The score assigned to each MEP combines his/her commitment to a certain topic and the amount of parliamentary questions produced by every member.
Click to read our methodology in detail. Last Updated: 2017-10-16