Malte Bonart

André Calero Valdez, Lena Adam, Dennis Assenmacher et al.

The digitization of the world has also led to a digitization of communication processes. Traditional research methods fall short in understanding communication in digital worlds as the scope has become too large in volume, variety, and velocity to be studied using traditional approaches. In this paper, we present computational methods and their use in public and mass communication research and how those could be adapted to professional communication research. The paper is a proposal for a panel in which the panelists, each an expert in their field, will present their current work using computational methods and will discuss transferability of these methods to professional communication.

Malte Bonart, Anastasiia Samokhina, Gernot Heisenberg et al.

Survey-based studies suggest that search engines are trusted more than social media or even traditional news, although cases of false information or defamation are known. In this study, we analyze query suggestion features of three search engines to see if these features introduce some bias into the query and search process that might compromise this trust. We test our approach on person-related search suggestions by querying the names of politicians from the German Bundestag before the German federal election of 2017. This study introduces a framework to systematically examine and automatically analyze the varieties in different query suggestions for person names offered by major search engines. To test our framework, we collected data from the Google, Bing, and DuckDuckGo query suggestion APIs over a period of four months for 629 different names of German politicians. The suggestions were clustered and statistically analyzed with regards to different biases, like gender, party, or age and with regards to the stability of the suggestions over time.

Malte Bonart, Philipp Schaer

This short paper deals with the combination and comparison of two data sources: Search engine results and query suggestions for 16 terms related to political candidates and parties. The data was collected before the federal election in Germany in September 2017 for a period of two months. The rank biased overlap (RBO) statistic is used to measure the similarity of the top-weighted rankings. For each search term and for both the search results and query auto-completions we study the stability of the rankings over time.