Chatbots and Social Bots in Corporate Communications

Contact

Prof. Dr. Stefan Stieglitz, Akademische Gesellschaft

Prof. Stefan Stieglitz
stefan.stieglitz@uni-potsdam.de


About the research project

Titel: The power of bots: The benefits and pitfalls of automation in corporate communication

Team: Prof. Stefan Stieglitz, Florian Brachten (University of Duisburg-Essen)

Project period: 2018 – 2020

Automation opens up many new applications for corporate communications. For example, chatbots can be used to automate simple or complex communication processes, such as responding to customer inquiries. Chatbots can also support information retrieval or collaboration across the organization.

However, there are also problematic forms of bots in social media, so-called social bots, which act like human actors. There is a risk that social bots can be used to negatively influence communication and the perception of products or companies in social media. In order to better understand the potential uses and dangers of bots in corporate communications, a team from the University of Duisburg-Essen has studied these forms of automated communication in a research project.

Content

Chatbots

  • What potential do automated applications have for communications departments?
  • How can chatbots be set up or improved?
  • What hurdles must be overcome?

Social Bots

  • To what extent do social bots try to influence the communication of companies in social media?
  • How can communications departments deal with this threat?
  • What is the legal framework?

Methodology

  1. First, a workshop was held to identify relevant topics and areas where bots are being used in an organizational environment based on previous research. The results were then used to guide ten interviews with representatives of ten organizations.
  2. The second part of the research project examined whether bots are used in social media to influence the social media reporting of DAX 30 companies in Germany. More than 10 million posts from 30 companies on Twitter and YouTube and 25 companies on Facebook were analyzed using the networks’ APIs.

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