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Finding the Sources and Targets of Subjective Expressions

  • As many popular text genres such as blogs or news contain opinions by multiple sources and about multiple targets, finding the sources and targets of subjective expressions becomes an important sub-task for automatic opinion analysis systems. We argue that while automatic semantic role labeling systems (ASRL) have an important contribution to make, they cannot solve the problem for all cases. Based on the experience of manually annotating opinions, sources, and targets in various genres, we present linguistic phenomena that require knowledge beyond that of ASRL systems. In particular, we address issues relating to the attribution of opinions to sources; sources and targets that are realized as zero-forms; and inferred opinions. We also discuss in some depth that for arguing attitudes we need to be able to recover propositions and not only argued-about entities. A recurrent theme of the discussion is that close attention to specific discourse contexts is needed to identify sources and targets correctly.

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Author:Josef RuppenhoferGND, Swapna Somasundaran, Janyce Wiebe
Parent Title (English):Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)
Document Type:Conference Proceeding
Year of first Publication:2008
Date of Publication (online):2016/10/06
Tag:machine learning; opinion mining
GND Keyword:Automatische Sprachanalyse; Semantische Analyse
First Page:2781
Last Page:2788
DDC classes:400 Sprache / 410 Linguistik
Open Access?:ja
Licence (German):License LogoUrheberrechtlich gesch√ľtzt