Audience fragmentation has long been feared to result from an increasing fragmentation of content supply. In the Internet age, the debate has become even more heated due to the explosion in content and the changes in the way content is presented and distributed. From the user's point of view, online media provide far more opportunities to practice active selection and thus more interest-based news consumption. In terms of democratic theory, the hypothesized consequences of individualized news consumption are predominantly negative: A fragmentation of audiences is believed to increase the risk of societal disintegration. In addition to active selection by media users, subtle and technically controlled pre-selection now also plays an important and hitherto largely unexplored role. Information intermediaries such as search engines, news aggregators and social networks act as brokers between the media content supply and the user, unconsciously guiding the latter in her choice of news. By collecting, structuring, weighting and aggregating content, they control the degree to which issues are encountered. For the users, they act as welcome orientation and navigation aids. At the same time, they influence these users through algorithm-based weighting logics such as the personalization of search results. Although the current debate on the societal role of information intermediaries is almost exclusively critical, there is a scarcity of clear evidence of both negative and positive effects.
The extent to which automated selection mechanisms reinforce or mitigate fragmentation tendencies is therefore an open question. The project aims to close this research gap. The goal of the study is therefore to determine the influence of the different weighting logics of the intermediaries, individually and in combination, on the degree of fragmentation of the audience. In theoretical terms, the project is based on a network-theoretical modelling of individual content selection on several levels of analysis, which makes the influence of the intermediaries visible. The empirical core of the project is an innovative combination of methods: By means of a content analysis, the journalistic range of topics of the most important German online news media is analyzed, and by means of representative tracking data, the extent to which users are actually confronted with these topics is investigated. This combination of methods enables the study to provide a picture of the diversity of supply and exposure diversity or fragmentation for the first time and to make a realistic assessment of the much-discussed filter bubble. It thus contributes to measuring the effects of algorithm-based news consumption via search engines or social networks on society as a whole.
Head of project:
Prof. Dr. Birgit Stark
Project staff:
Dr. Pascal Jürgens
Funding:
German Research Foundation (STA 1437/3-1)
Period: 2017-2021