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Purpose The purpose of this paper is to investigate to what extend an automated, algorithm-based analysis of online conversations of stakeholders in social media and other Internet media can be used for reputation management. Design/methodology/approach Examination of the reputation of the 5,000 companies with the largest number of employees in Germany based on communication with these companies in 350m online sources on the German-speaking Internet within one year. The method is grounded on an adapted reputation model based on Fombrun. Findings The central result of the study is the identification of the ideal balance between the different dimensions leading to the best overall reputation. The resulting correlation matrix with the respective correlation coefficients (according to Pearson) thus forms the basis for the optimal reputation architecture. Research limitations/implications The discovered “optimal reputation architecture” refers to a German context. Future studies should investigate in how far the adapted model and the “optimal reputation architecture” also work for other cultures. It can be assumed that there may be differences as different dimensions, for example, sustainability, may have a different importance in other cultural contexts. Apart from the question if the “optimal reputation architecture” is also valid for other cultural contexts, the concept has to be validated for German companies as well as it is just based on the two described studies. Practical implications The method used shows that social listening can deliver valuable results for research in the field of reputation management as it expands the possibilities to investigate reputation on a large scale. The approach shows in how far scientific research can be expanded beyond classic content analysis as the number of items which can be analysed exceeds that of classic analytical approaches by far. Explicit and implicit experiences, which are the drivers of reputation, can be systematically recorded and analysed using social listening, thus delivering valuable insights in how stakeholders perceive the performance of a company in different dimensions. Social implications Measuring the reputation on the basis of social listening is very important for practical applications in companies, because the data is available digitally and can deliver up-to-date reputation values almost in real time – so that the communication can be aligned very quickly with current events. This makes it easier to implement and control the interaction between companies and their environment in the digital space. Originality/value The classic approach in reputation management is traditional market research. It is relatively expensive and takes a relatively long time to produce results. Reputation management based on social listening digitises reputation measurement, lowers costs and delivers results in a very timely manner. It might be the future of reputation measurement. This is relevant not only for practical purposes but also for scientific approaches.
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