The purpose of the bachelor thesis with the working title "Benchmarking Clustering Algorithms for the Creation of Macro-Clusters for a Two-Step Stream Clustering Algorithm" is to determine the most fitting clustering techniques for producing macro- clusters within a two-step stream clustering. In order to accomplish this, the main objective of this thesis is to benchmark various clustering techniques and evaluate the outcomes using selected evaluation metrics. Moreover, this thesis will concentrate on textual data taken from social media campaigns. Recognizing the unnoticed importance of the offline phase, this bachelor thesis focuses on benchmarking the traditional clustering algorithms to be used in the offline phase to summarize the micro-clusters created in the online phase and aims to determine which clustering techniques, within a two-step stream clustering framework, are best appropriate.