Tassilo Elsberger

Tassilo Elsberger

Master's Thesis

Analysis of Artificial Intelligence Trends In German Economics and Politics - A Data-Driven Approach


Philipp Dumbach (M.Sc.), Leo Schwinn (M.Sc.), Prof. Dr. B. Eskofier


11 / 2021 – 06 / 2021


With the ever growing advances in modern research in computer science, buzzwords like Artificial
Intelligence (AI), Machine Learning (ML) and Deep Learning (DL) are getting more and
more attention in academia [1]. According to the Artificial Intelligence Index Report 2019, the
amount of peer reviewed AI related journal publications worldwide has tripled between 1998 and
2018 [2].
The development process of new technologies is usually a combination of scientific and industrial
research with its intensity varying from field to field [3]. Therefore, it is important to understand
scientific trends and adequately respond to them as they often evolve into new technologies, which
is important for both politics and economics [4, 5]. So far most research in this field has dealt
with buzzword detection, importance or development in various media like blogs, news articles
and websites [6, 7, 8, 9]. However, a lack of publications in trend analysis has been registered in
the political context and especially regarding the correlation between business and politics. This
correlation is also important to consider regarding cases of lobbyism in Germany [10].
In this thesis, a comparison of Artificial Intelligence trends between German economic journals
and political protocols is performed.



[1] Ongsulee, P.: Artificial intelligence, machine learning and deep learning. 15th International
Conference on ICT and Knowledge Engineering, 2017

[2] Perrault et al.: Artificial Intelligence Index Report 2019. Stanford University, 2019.

[3] Fleming, L., Sorenson, O.: Science as a map in technological search. Strategic Management
Journal, 25: 909-928, 2004

[4] Oliner, S. D., Sichel, D. E. The Resurgence of Growth in the Late 1990s: Is Information
Technology the Story? Journal of Economic Perspectives Vol. 14, No 4, Fall 2000.

[5] Fast, E., Horvitz, E.: Long-Term Trends in the Public Perception of Artificial Intelligence.
arXiv:1609.04904[cs.CL], 2016.

[6] Nakajima et al.: Early detection of buzzwords based on large-scale time-series analysis of
blog entries. HT ’12: Proceedings of the 23rd ACM conference on Hypertext and social
media, Page 275-284, June 2012

[7] Ishikawa, Y., Hasegawa, M.: T-Scroll: Visualizing Trends in a Time-Series of Documents ofr
Interactive User Exploration. ECDL 2007: Research and Advanced Technology for Digital
Libraries pp 235-246, 2007

[8] Caled et al.: Buzzword detection in the scientific scenario. Pattern Recognition Letters
Volume 69, 1 January 2016, Pages 42-48, January 2016

[9] Mjos et al.: The functions of buzzwords: A comparson of ’Web 2.0’ and ’telematics’. First
Monday, Volume 19, Number 12-1, December 2014

[10] Heinze, R.: Staat und Lobbyismus: Vom Wandel der Politikberatung in Deutschland.