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Analyzing clusters and constellations from untwisting shortened links on Twitter using conceptual graphs


Reference:

Tonkin, E.L., Pfeiffer, H. D. and Tourte, G. J. L., 2013. Analyzing clusters and constellations from untwisting shortened links on Twitter using conceptual graphs. In: Pfeiffer, H. D., Ignatov, D. I., Poelmans, J. and Gadiraju, N., eds. Conceptual Structures for STEM Research and Education. Berlin: Springer, pp. 58-74. (Lecture Notes in Computer Science; 7735)

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Official URL:

http://dx.doi.org/10.1007/978-3-642-35786-2_6

Abstract

The analysis of big data, although potentially a very rewarding task, can present difficulties due to the complexity inherent to such datasets. We suggest that conceptual graphs provide a mechanism for representing knowledge about a domain that can also be used as a useful scaffold for big data analysis. Conceptual graphs may be used as a means to collaboratively build up a robust model forming the skeleton of a data analysis project. This paper describes a case study in which conceptual graphs were used to underpin an exploration of a corpus of tweets relating to the Transportation Security Administration (TSA). Through this process we will demonstrate the emerging model built up of the data landscape involved and of the business structures that underlie the technical frameworks relied upon by microblogging software.

Details

Item Type Book Sections
CreatorsTonkin, E.L., Pfeiffer, H. D. and Tourte, G. J. L.
EditorsPfeiffer, H. D., Ignatov, D. I., Poelmans, J. and Gadiraju, N.
DOI10.1007/978-3-642-35786-2_6
Research CentresUKOLN
StatusPublished
ID Code38049

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