Dynamics in Search Engine Query Suggestions for European Politicians
Franziska Pradel, Fabian Haak, Sven-Oliver Proksch, Philipp Schaer
TL;DR
This study analyzes Google search query suggestions for European politicians across ten countries during the 2019 European Parliament election period to assess latent political interest. Using two-week aggregated data for 793 politicians and measuring stability and cross-country similarity with the $Jaccard$ coefficient, the authors relate these dynamics to meta-attributes via regression. Key findings show that in-country searches, lead-candidate status, government affiliation, and female gender reduce stability, while male gender and government roles increase cross-country similarity; lead candidates and right-leaning ideologies tend to lower cross-national similarity. The work highlights that national context drives online political information seeking and suggests avenues for future cross-platform and personalization research, with implications for understanding the European public sphere and politicization online.
Abstract
Search engines are commonly used for online political information seeking. Yet, it remains unclear how search query suggestions for political searches that reflect the latent interest of internet users vary across countries and over time. We provide a systematic analysis of Google search engine query suggestions for European and national politicians. Using an original dataset of search query suggestions for European politicians collected in ten countries, we find that query suggestions are less stable over time in politicians' countries of origin, when the politicians hold a supranational role, and for female politicians. Moreover, query suggestions for political leaders and male politicians are more similar across countries. We conclude by discussing possible future directions for studying information search about European politicians in online search.