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

该项目的总体目标是从参与的利益相关者的角度描述和解释搜索引擎优化(SEO)的作用。这是通过分析搜索结果和搜索引擎结果页面的优化内容以及对搜索引擎用户、搜索引擎优化器和内容提供商的定量和定性调查来实现的。在第一个项目阶段成果的基础上，目标如下：(1)扩展和完善搜索结果的自动分析(增加更多指标、改进权重、机器学习)，(2)进行大型实证研究，以衡量SEO对与意见形成相关的主题的影响，(3)扩大对SEO的理解，将非商业内容提供商以及搜索引擎提供商的视角包括在内。在该项目的第二阶段，我们将进一步完善最初对信息性内容的关注，重点放在与意见形成相关的四个领域：健康、环境、消费者保护和政治。对于这些与社会相关的领域，我们将使用主题相关的搜索查询及其频率创建广泛的搜索集群。在实证研究中，我们将分析增发对这些领域的影响。利用现在得到改进的软件，将进行大规模的经验性研究，真实地反映搜索查询和搜索频率。搜索结果的精细化自动分析允许更精确地衡量搜索引擎优化的影响，从而量化其影响。就像在第一个项目阶段一样，该项目的特点是结合了计算机科学、信息科学和社会科学的方法。通过将技术分析的结果与社会科学研究的结果进行三角划分，我们的目标是获得更深刻的见解。通过将外部兴趣对搜索结果的影响包括在内，可以开发出一种新的信息搜索模型，该模型可以反映参与者(特别是用户和搜索引擎提供商)更现实的行为。在转移到实践的层面上，结果将与消费者保护等事项相关。

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.