Andreas Jungherr
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21 Oct 2020
Andreas Jungherr Publications
2020/10/21 Andreas Jungherr

New Publication: Computational Social Science and the Study of Political Communication

New journal article in Political Communication with Yannis Theocharis. In the introduction to our upcoming special issue on the use of computational methods in communication science, we discuss the underlying conceptual, methodological, and institutional challenges to their integration in the field.

If you are wondering what exactly Computational Social Science or Computational Communication Science are supposed to be, we provide this definition:

We define computational social science as an interdisciplinary scientific field in which contributions develop and test theories or provide systematic descriptions of human, organizational, and institutional behavior through the use of computational methods and practices. On the most basic level, this can mean the use of standardized computational methods on well-structured datasets (e.g., applying an off-the-shelf dictionary to calculate how often specific words are used in hundreds of political speeches), or at more advanced levels the development or extensive modification of specific software solutions dedicated to solving analytically intensive problems (e.g., from developing dedicated software solutions for the automated collection and preparation of large unstructured datasets to writing code for performing simulations). Accordingly, CCS, and by extension Computational Political Communication, lie at the intersection of CSS and (political) communication, with a topical focus on theories and phenomena associated with communicative channels, objects, behavior, and effects.

More specifically:

It might be helpful to focus more on studies and research projects in which computational methods and practices are not used as plug-and-play solutions but instead demand for varying degrees of customization with regard to data collection, preparation, analysis, or presentation. Again, this is best thought of as a distinction in degree. On one end of the scale, we find projects that require some coding with regard to the sequential calling of preexisting or slightly modified functions or data management. On the other end of the scale we find research projects that demand the development of dedicated software solutions, for example, in automated and continuous data collection, preparation and structuring of large unstructured raw data, or the development of dedicated non-standardized analysis procedures. Projects at different ends of this scale share issues arising from their focus on social behavior, systems, or phenomena but they vary significantly with regard to their computational demands. Projects that use standardized computational methods might thus be basically indistinguishable from other areas in empirical social science research. On the other hand, projects at the other end of the scale are likely to face challenges indistinguishable from software development in computer science.

Now, if this feels like it could be of interest to you, have a look at the abstract or move directly to the article.

Abstract: The challenge of disentangling political communication processes and their effects has grown with the complexity of the new political information environment. But so have scientists’ toolsets and capacities to better study and understand them. We map the challenges and opportunities of developing, synthesizing, and applying data collection and analysis techniques relying primarily on computational methods and tools to answer substantive theory-driven questions in the field of political communication. We foreground the theoretical, empirical, and institutional opportunities and challenges of Computational Communication Science (CCS) that are relevant to the political communication community. We also assess understandings of CCS and highlight challenges associated with data and resource requirements, as well as those connected with the theory and semantics of digital signals. With an eye to existing practices, we elaborate on the key role of infrastructures, academic institutions, ethics, and training in computational methods. Finally, we present the six full articles and two forum contributions of this special issue illustrating methodological innovation, as well as the theoretical, practical, and institutional relevance and challenges for realizing the potential of computational methods in political communication.

Yannis Theocharis and Andreas Jungherr. 2020. Computational Social Science and the Study of Political Communication. Political Communication. doi: 10.1080/10584609.2020.1833121 (Online First).

CCS, Computational Communication Science, Computational Social Science, CSS, Political Communication
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