Sentiment Analysis of Social Media for Evaluating Universities

Anas Abdelrazeq (), Daniela Janßen, Christian Tummel, Sabina Jeschke and Anja Richert
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Anas Abdelrazeq: IMA/ZLW & IfU, RWTH Aachen University
Daniela Janßen: IMA/ZLW & IfU, RWTH Aachen University
Christian Tummel: IMA/ZLW & IfU, RWTH Aachen University
Sabina Jeschke: IMA/ZLW & IfU, RWTH Aachen University
Anja Richert: IMA/ZLW & IfU, RWTH Aachen University

A chapter in Automation, Communication and Cybernetics in Science and Engineering 2015/2016, 2016, pp 233-251 from Springer

Abstract: Abstract In the age of digitalization, a huge amount of sentiments are expressed daily on university related topics using social media platforms. Particularly, posted statements from students and teachers can provide a potential source for evaluating universities. Twitter as one of the most popular microblogging platforms is a rich data resource for opinion mining. Stimulated by this fact, ways to analyze Twitter for information in the context of universities are sought. This paper looks at the analysis of social media sentiment as a complementary source for evaluating universities. The extracted results can support university rankings that experience criticism in terms of measuring vital indicators. This paper relays on sentiment analysis methods to analyze opinions published on Twitter. For this purpose, at first, tweets that are related to selected universities in Germany were collected. Second, the tweets were classified based on their sentiment into “Positive” and “Not Positive” tweets. At last, the results were analyzed providing information about the communicative topics at the universities. This paper gives an outlook to further research in context of an automated analysis of social media content in order to support the evaluation of universities.

Keywords: Social Media; Universities; Higher Education; Twitter; Sentiment Analysis; Data Analysis; Natural Languages Processing; Learning Environments (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/978-3-319-42620-4_19

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