Using Textual Emotion Extraction in Context-Aware Computing

Daubenschütz, Tim (2015) Using Textual Emotion Extraction in Context-Aware Computing. Bachelor thesis, Institute of Databases and Information Systems.

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In 2016, the number of global smartphone users will surpass 2 billion. The common owner uses about 27 apps monthly. On average, users of SwiftKey, an alternative Android software keyboard, type approximately 1800 characters a day. Still, all of the user-generated data of these apps is, for the most part, unused by the owner itself. To change this, we conducted research in Context-Aware Computing, Natural Language Processing and Affective Computing. The goal was to create an environment for recording this non-used contextual data without losing its historical context and to create an algorithm that is able to extract emotions from text. Therefore, we are introducing Emotext, a textual emotion extraction algorithm that uses conceptnet5’s realworld knowledge for word-interpretation, as well as Cofra, a framework for recording contextual data with time-based versioning.

Item Type: Thesis (Bachelor)
Subjects: DBIS Research > Master and Phd-Thesis
Divisions: Faculty of Engineering, Electronics and Computer Science > Institute of Databases and Informations Systems > DBIS Research and Teaching > DBIS Research > Master and Phd-Thesis
Depositing User: Herr Marc Schickler
Date Deposited: 13 May 2015 16:32
Last Modified: 13 May 2015 16:32

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