Analyzing the Twitter Data Stream Using the Snap! Learning Environment

• Published in: Informatics in Schools. Curricula, Competences, and Competitions Vol. 9378; pp. 155 - 164
• Main Authors: Grillenberger, Andreas, Romeike, Ralf
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2015; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Big Data; CS Education; Data Management; Data Stream Systems; Educational equipment & technology, computer-aided learning (CAL); Ethical & social aspects of computing; Real–Time Data Analyses; Teaching of a specific subject; Twitter
• ISBN: 9783319253954; 3319253956
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-319-25396-1_14

In the last few years, tremendous changes have occurred in the field data management, especially in the context of big data. Not only approaches for data analysis have changed, but also real–time data analyses gain in importance and support decision–making in various contexts. One of the most exciting approaches for processing and analyzing large amounts of data in nearly real–time are data stream systems. In this paper, we will demonstrate how such developments in CS can be introduced in CS education by using data stream systems as an example. We will discuss these systems from a CS education point of view and describe an approach for carrying out data stream analysis by using the Twitter stream as data source. Also, we will show how the programming tool Snap! can be extended for supporting teaching in this context.