Guiding Theme A3: Opinion and Sentiment - extrapropositional aspects of discourse

Guiding theme A3 analyzes extra-propositional aspects of meaning: distinguishing facts from non-facts and classifying sentiment associated with an entity (A1) or an event (A2). These aspects of meaning can help identifying entities or facts in a given text that the writer of the text considers important in that he or she conveys an opinion or sentiment towards them.

Analysis of modality and sentiment can thus serve as a guide for content extraction for summarization and directly feeds into aspect-based summarization or argument analysis, which aims to highlight different perspectives and opinions about specific contents, or the pros and cons of a situation.

This guiding theme will closely interact with themes A1 and A2 in Area A and with B2 in Area B.

Poster (in German)

Example thesis topics

  • Sentiment and opinion in discourse graphs
  • Sentiment and opinion in extended contexts
  • Motifs over sentiment and opinion in aspect-oriented multi-document summarizations

References

[1] Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher D. Manning, Andrew Ng, Christopher Potts (2013): Recursive Deep Models for Sentiment Compositionality Over a Sentiment TreebankProceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, Seattle, Washington, USA.

Pang, B. und Lee, L. (2008). Opinion Mining and Sentiment Analysis. Foundations and Trends in Information Retrieval, 2(1–2):1–135.

Liu, B. (2012). Sentiment Analysis and Opinion Mining. Morgan & Claypool Publishers.

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