Bachelor Thesis BCLR-2022-23

BibliographySchmidt, Joshua: Ranking universities based on academic reputation and exploring potential correlations to their success on social media.
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Bachelor Thesis No. 23 (2022).
45 pages, english.

Purpose - The idea behind this research is to provide two things: A sophisticated university ranking based on academic reputation for institutions all across the globe, as well as using that ranking to collect relevant data from various Social Media platforms for each university listed. We hope to find correlations between academic reputation and success on Social Media. If we do, we can use Social Media data to improve upon established ranking systems. The ranking data could then be used to help automate the process of evaluating incoming applications from students all over the world. Methodology - We collect ranking data from four big international rankings for universities in the area of Computer Science: Times Higher Education World University Rankings, QS World University Ranking, ShanghaiRanking Academic Ranking of World Universities and Round University Rankings. The data is normalized and combined into an overall ranking. To explore potential correlations with success on Social Media, we also collect data concerning each of the universities in our ranking for Facebook, YouTube, Instagram and Twitter and calculate Spearman’s rank correlation coefficient for each platform individually. Findings - Analyzing the data, we find positive correlations between how universities rank in the established ranking systems and how well their Social Media accounts are performing. Due to the high number of institutions we look at, we find a high statistical significance as well, leading us to believe that a causal association exists. Value - The overall ranking we create ranks over 1200 universities from all over the globe. The positive correlations between academic reputation and success on Social Media suggests that we can make use of the data collected from both the traditional rankings as well as the Social Media metrics to provide assistance when it comes to evaluating universities in the future. This study also provides a Graphical User Interface to easily work with this data going forward.

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Department(s)University of Stuttgart, Institute of Architecture of Application Systems
Superviser(s)Aiello, Prof. Marco
Entry dateOctober 21, 2022
   Publ. Computer Science