Tassilo Elsberger

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

Duration
11 / 2021 – 06 / 2021

Abstract
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.

References:
[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 for 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.