Abstract
The field of opinion mining provides a multitude of methods and techniques to be utilized to find, extract and analyze subjective information, such as the one found on social media channels. Because of the differences between these channels as well as their unique characteristics, not all approaches are suitable for each source; there is no “one-size-fits-all” approach. This paper aims at identifying and determining these differences and characteristics by performing an empirical analysis as a basis for a discussion which opinion mining approach seems to be applicable to which social media channel.
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Petz, G., Karpowicz, M., Fürschuß, H., Auinger, A., Stříteský, V., Holzinger, A. (2013). Opinion Mining on the Web 2.0 – Characteristics of User Generated Content and Their Impacts. In: Holzinger, A., Pasi, G. (eds) Human-Computer Interaction and Knowledge Discovery in Complex, Unstructured, Big Data. HCI-KDD 2013. Lecture Notes in Computer Science, vol 7947. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39146-0_4
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DOI: https://doi.org/10.1007/978-3-642-39146-0_4
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