The Role of Predicates in Opinion Holder Extraction
Michael Wiegand and Dietrich Klakow
In: RANLP-Workshop on Information Extraction and Knowledge Acquisition, 16 Sept 2011, Hissar, Bulgaria.
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.