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Slides: Context Aware Sentiment Detection

Weichselbraun, Albert (2011) Slides: Context Aware Sentiment Detection. In: Research Seminar, 10 February 2011, Curtin University, Perth, Australia. (Unpublished)

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The simplicity of using Web publishing services and social networking platforms has resulted in an abundance of user-generated content. A significant portion of this content contains user opinions with clear economic relevance - customer and travel reviews, for example, or the articles of respected bloggers who influence purchase decisions. Analyzing and acting upon user-generated content is therefore becoming imperative for marketers and social scientists who need to gather feedback from very large user communities. In order to identify trends in user-generated content and compare differing perceptions of interest groups, automated sentiment detection identifies and aggregates polar opinions (i.e. positive or negative statements about facts). For achieving accurate results, sentiment detection requires a correct interpretation of natural languages, which remains a challenging task due to their inherent ambiguities. Most approaches to sentiment detection are based on the notion that there is a stable conceptual connection between words and their adjacent text, but neglect the context of opinionated terms when trying to resolve ambiguities. To address this limitation, the presenters will discuss an approach based on contextualized sentiment lexicons and introduce a domain-specific method for the automated refinement of such lexicons.

Item Type:Conference or Workshop Item (Speech)
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
ID Code:28
Deposited By: Dr Albert Weichselbraun
Deposited On:10 Feb 2011 09:28
Last Modified:10 Feb 2011 09:28

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