State advertising as an instrument of transformation of the media market in Hungary
Category: Best visualization (small and large newsrooms)
Organisation: ATLO Team / Átlátszó
Organisation size: Small
Publication date: 9 Jul 2019
Credit: Attila Bátorfy, Ágnes Urbán
The submitted project is an appendix to our journal paper “State advertising as an instrument of transformation of the media market in Hungary” , published in East European Politics. In the paper we examine and analyze data on state bodies’ (the government, ministries, authorities, state institutions, state owned companies) advertising practices between 2006 and 2018 through three following governments.
The submitted project and it’s appendix is the last phase of our ongoing scientific investigation on the allocation state advertising expenditures in Hungary started in 2016. Our work is often cited not only by news media but also journal papers and at last the regulation of state advertising is on the agenda of the European Commission.
We use data obtained from market research company Kantar and we store it in Google Spreadsheet. For the visualization we used Tableau before, but for the submitted project we used Flourish.
What was the hardest part of this project?
The methodology is the hardest part because we needed to avoid vague arguments on which media outlets can be considered as “pro-government”. The importance of this project is that we have enough big data on proving the anti-market and anti-competition nature of public funding of the media in forms of state advertising. We always stated that the corrupted allocation of state advertising is not only an academic question, that’s why we used visualizations for the general public. We also think that our project is a good example of the collaboration of the academia, journalism and visualization.
What can others learn from this project?
We truly believe that same amount of data could reveal similar hidden patterns also in those countries where the state’s and the government’s influence on media is considered low. We helped in data requests and analysis our Polish and Czech colleagues.