PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Prototypical Opinion Holders: What We can Learn from Experts and Analysts
Michael Wiegand and Dietrich Klakow
In: RANLP 2011, 12 Sept - 14 Sept 2011, Hissar, Bulgaria.

Abstract

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 labeled 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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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Natural Language Processing
ID Code:8856
Deposited By:Diana Schreyer
Deposited On:21 February 2012