Oliver Pollex

The potential of Micro-Targeting in Italian electoral campaigns

The way how political campaigns are conducted has changed substantially within the last decade. A significant trend in political communication is the use of social media in combination with micro-targeting techniques. Through micro-targeting politicians and political parties try to identify the right target audience and spread their specific political messages. These personalized advertisements are nuanced to reflect the way in which the audience sees the world, regarding values, attitudes and behavior. It is difficult to reliably define the relevance and scope of micro-targeting, because no comprehensive study has proved its effectiveness (Jungherr, 2017) and political actors are not required to publicly give notice of the use of micro-targeting in their campaigns. With the assumption that micro-targeting is an effective tool for communication with the electorate, the presentation analyses, if the conditions for a wide scale application of micro targeting in the German electoral process do or do not exist. The analysis is based on three indicators: data availability (such as in the protection of personal data through a legal framework), indecisiveness of the electorate (such as the volatility of election results) and the use of social media. The Analysis will show that the conditions for a wide scale application of micro-targeting in Germany exist mostly for the big internet platforms such as Google and Facebook. Political parties and other smaller entities will therefore in the future be driven to rely on the micro-targeting services offered by big internet platforms for political advertisement. Jungherr A. (2017) Einsatz Digitaler Technologie im Wahlkampf. Schriftreihe Medienkompetenz 10111: 92–101.

Oliver Pollex

Oliver Pollex studies political sciences at the Technical University of Munich, the Bavarian School of Public Policy and the Università di Pavia. His research focuses on the influence of digital technologies such as artificial intelligence, machine learning or social media on politics and society. He also concentrates on algorithmic analyses of big data to answer questions regarding political science