In times of Brexit and Trump, trade policy in general and the external trade policy of the European Union (EU) in particular has increasingly become the subject of public attention. Moreover, some trade negotiations conducted by the EU, the world's largest trading entity, have recently become subject to unprecedented politicization. Not only has attention for them increased, opinions about their desirability and content have also become more polarized, and more actors have participated in that political process than in the past. Strikingly however, negotiations with Canada (CETA) and the United States (TTIP) were far more controversial than similar trade agreement negotiations with Japan or Vietnam.
In fact, while some particular trade deals have been marked by a high degree of polarized public input from a broad range of actors, many similar and even more comprehensive trade deals seem have to escaped detection. A scholarly consensus is emerging in terms of how to define and measure politicization but no systematic undertaking has thus far been applied to the various trade deals pursued by the EU since it lifted its moratorium on bilateral trade negotiations ion 2005. The purpose of this project is to fill this research gap by mapping the extent to which these trade deals have become politicized – geographically as well as temporally.
Combining state-of-the-art social listening algorithms with traditional media analysis, this project will contribute to the study of politicization by presenting an empirical comparison of all cases in this particular field with regard to their salience, the degree of polarisation of opinions about issues in them, and the (amount of) actors involved in that process. The project thus seeks to do the empirical groundwork and pave the way for further future research on how different structural factors could be said to contribute to this phenomenon. Furthermore, the geographic and temporal aspects will give valuable original insights into how the dynamic process of politicization occurs and is autoreferentially amplified through new-media cycles.