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Prototypical Opinion Holders: What We can Learn from Experts and Analysts

  • In order to automatically extract opinion holders, we propose to harness the contexts of prototypical opinion holders, i.e. common nouns, such as experts or analysts, that describe particular groups of people whose profession or occupation is to form and express opinions towards specific items. We assess their effectiveness in supervised learning where these contexts are regarded as labelled training data and in rule-based classification which uses predicates that frequently co-occur with mentions of the prototypical opinion holders. Finally, we also examine in how far knowledge gained from these contexts can compensate the lack of large amounts of labeled training data in supervised learning by considering various amounts of actually labeled training sets.

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Author:Michael WiegandGND, Dietrich Klakow
Parent Title (English):Proceedings of the International Conference on Recent Advances in Natural Language Processing 2011, Hissar, Bulgaria, 12-14 September, 2011
Publisher:Incoma Ltd.
Place of publication:Shoumen
Editor:Galia Angelova, Kalina Bontcheva, Ruslan Mitkov, Nikolai Nikolov
Document Type:Conference Proceeding
Year of first Publication:2011
Date of Publication (online):2019/02/04
Tag:Expertenmeinung; Sentimentanalyse
GND Keyword:Computerlinguistik; Information Extraction; Maschinelles Lernen; Text Mining
First Page:282
Last Page:288
DDC classes:400 Sprache / 400 Sprache, Linguistik
Open Access?:ja
Licence (English):License LogoCreative Commons - Attribution-NonCommercial-ShareAlike 3.0 Unported