References

Good work is never done alone.

This page contains all the resources – like programming languages, libraries, or APIs – which we used to build Europinion. Further, the list contains all literature which guided us through making some elementary decisions for the structure of Europinion.

Reasoning

ec.europa.eu/eurostat - This is a subpage of the European Commission which contains extensive data about Europe. We used a table which contains statistics about the population size of EU nations.
europal.europa.eu - This is the official webpage of the European Parliament. We used this page to acquire information about the Distribution of Seats and to understand how the elections are named in the 24 official languages. For this we visited the subpage, which referes to the European elections, in each language.
Hashtag – We have handled hashtags based on "Interpreting Hashtag Politics: Policy Ideas in an Era of Social Media" by Stephen Jeffares (link).

Technology

Atom - The best text editor deserves credits.
Fuseki - Apache Jena Fuseki is a SPARQL server which we used to query our dataset.
Python - We just love Python, but we love the community behind it even more. Those people provided us with the beautiful libraries Pandas, RDFLib, Tweet Preprocessor, TwitterAPI package, and some others.
JavaScript - Thanks to the JavaScript Libraries Chart.js and D3.js we could create interactive and dynamic visualisations of our data.
Sentilo - Sentilo is a API which offers sentence-based sentiment analysis. It relies on FRED, a machine read for the Semantic Web.
Twitter - Twitter is a social networks in which people primarily express their opinion in short messages, so called Tweets. This data can be acquired with the Twitter API.
Yandex - Yandex is the Russian equivalent to Google. While Google monetizes nearly all APIs and other services, Yandex offers a free Translate API.