Analysing party preferences using google trends

The formation of party preferences is a complex and not yet fully understood process based on a number of factors. This process, which is of great interest for both social and political science, is usually studied using questionnaire data which has proven to be a very reliable yet often costly and limited approach. Advances in technology and the rise of the internet as a primary information source for many people have created a new approach to keep track of peoples interests. The major gateways to the internets information are the so-called search engines, and Google, arguably the most commonly used search engine, allows scientists to tap the vast source of information generated by its users search queries. In this paper we describe how this data source can be used to estimate the effect of different issues on party preferences using German voters and the German party system as an example. We find that using data provided by Google Trends can lead to a variety of interesting and occasionally counterintuitive insights into peoples party preferences

Bonn eXperimental System (BoXS): An open-source platform for interactive experiments in psychology and economics

The increased interest in complex-interactive behavior on the one hand and the cognitive and affective processes underlying behavior on the other are a challenge for researchers in psychology and behavioral economics. Research often necessitates that participants strategically interact with each other in dyads or groups. At the same time, to investigate the underlying cognitive and affective processes in a fine-grained manner, not only choices but also other variables such as decision time, information search, and pupil dilation should be recorded. The Bonn eXperimental System (BoXS) introduced in this article is an open-source platform that allows interactive as well as non-interactive experiments to be conducted while recording process measures very efficiently and completely browser-based. In the current version, BoXS has particularly been extended to enable conducting interactive eye-tracking and mouse-tracking experiments. One core advantage of BoXS is its simplicity. Using BoXS does not require prior installation for both experimenters and participants, which allows for running studies outside the laboratory and over the internet. Learning to program for BoXS is easy even for researchers without previous programming experience