Liegt die Zukunft der Kommunikationswissenschaft in der Vergangenheit? Ein Plädoyer für Kontinuität statt Veränderung bei der Analyse von Digitalisierung

At present, social changes are summarized under the term digitalization. At first glance, this requires the development of new concepts, theories, and methods. This article takes a critical look at this assumption. Perceived changes can be understood as an opportunity to work out the constants of human communication. To clarify this argument, in the first part of the article we compare two perspectives: digitalization as changes in reality versus digitalization as a changed view of reality.Digitization is the conversion of continuous signals into discrete signals. While this technical process is more or less irrelevant for communication science, the related social process is of particular concern. However, to a large extent, what constitutes the social side of digitization is unclear. So far, digitalization can probably best be understood as a form of mediatization. Since mediatization is regarded as a social metaprocess, the concept of digitalization lacks empirical substance and the definition of the term remains vague.Due to the lack of meaning, we view digitalization as a change in the way we observe things. From this perspective, we explain the popularity of the concept of digitalization with the help of organizational theories. Following neo-institutionalist arguments, the digitalization discourse can be understood as an identity-forming communication flow. This is reflected in the positioning of the players in the texts that preceded this article. Representatives of standardized social research and interpretative social research present their conceptions of the discipline. Moreover, digitalization can be seen as a rationalized myth. Such myths reflect the expectations of the environment; they are adopted without considering their efficiency. The discipline adopts the attribute, digital, because it has a high positive connotation in the environment of communication science. Ultimately, digitalization appears to be a kind of heuristic for structuring the field with political implications, but not as a theoretically valid research category.Assuming that digitalization is a rationalized myth, consequences can be drawn for the development of theory and methods. We prove the benefit of this changed perspective by discussing the constitutive concepts of communication science. On the theoretical side, many studies have investigated on the topic of public communication. One topos of this research is the blurring of boundaries, e.?g. between public and private or public and interpersonal communication. Instead of highlighting the changes, we seek to determine what remains constant. Traditionally, the public has been associated with mass media and social outcomes. Upon closer inspection and when considering basic communication models, this connection has always been problematic. The blur is caused by definitions of the term and not by changes in the social world. To solve this problem, we propose a redefinition of publicness at the level of interpersonal communication.Methodologically, many approaches have been developed over the past years. For example, webometrics, digital methods and computational methods are promising fields of innovation. However, it is completely unclear how these methods relate to classical methods, such as surveys, content analyses, or observations. If web mining is about tracking user behaviors (digital traces) that were not created for scientific research (process-generated data), it can be seen as a kind of observation. For example, log file analysis is characterized as an observation method in classical methodological textbooks. But the same criterion also applies to websites. Websites are artifacts of human behavior that, for the most part, are not produced for scientific purposes. However, their analysis is usually seen as content analysis, not as observation.This comparison of methods demonstrates that even the distinction between classical methods is unclear. To solve this problem, we propose to better differentiate the different levels involved in the research process. Data collection can be understood as the transfer of empirical facts into data by observation. Data preparation would then be the transformation of data into datasets. Content analysis is a type of data preparation technique. Data analysis transforms data sets into substantial statements about the world. For example, statistics are used for this purpose. New methods can be better located in these known categories. Webometrics, digital methods and computational methods are examples of the automation of the research pipeline components, e.?g. as automated data collection or automated data preparation.We conclude that focusing on continuity offers an opportunity to improve proven concepts and methods instead of replacing them with vague terms. Therefore, we plead for observing continuity in the context of change and not using digitalization and its inherent metaphor of transformation as a lens for analyzing social change.