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