SEO effect 2: A multi-perspective examination of search engine optimization's influence on search result quality and user behaviour

• Applicant: Professor Dr. Dirk Lewandowski
• Subject Area: Data Management, Data-Intensive Systems, Computer Science Methods in Business Informatics
• Term: since 2021
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 467027676

The general objective of the project is to describe and explain the role of search engine optimization (SEO) from the point of view of the participating stakeholders. This is done by analysing search results and search engine result pages for optimized content as well as the quantitative and qualitative surveying of search engine users, search engine optimizers and content providers. Building upon the results from the first project phase, the following sub-goals are targeted: (1) to extend and refine the automatic analysis of search results (adding more indicators, improved weightings, machine learning), (2) to conduct large empirical studies to measure the impact of SEO on topics relevant to opinion forming, (3) to broaden the understanding of SEO to include the perspectives of non-commercial content providers as well as search engine providers. In the second phase of the project, we will further refine the original focus on informative content by focusing on four areas relevant to opinion forming: Health, Environment, Consumer Protection and Politics. For these societally relevant areas, we will create extensive search clusters with thematically relevant search queries and their frequencies. In empirical studies, we will analyse the impact of SEO in these areas. With the now enhanced software, large-scale empirical studies will be conducted that realistically reflect search queries and search frequencies. The refined automatic analysis of search results allows to measure the influence of search engine optimization more precisely and thus to quantify its impact. Just as in the first project phase, the project is characterised by combining methods from computer science, information science and the social sciences. By triangulating the results of the technical analyses with those of the social science studies, we aim to gain more profound insights. By including the influence of external interests on search results, a new information-seeking model can be developed that reflects more realistic behaviour on the part of the actors (especially users and search engine providers). On the level of transfer into practice, the results will be relevant, among other things, for matters of consumer protection.

• DFG Programme: Research Grants