@inproceedings{WiegandKlakow2019, author = {Michael Wiegand and Dietrich Klakow}, title = {Prototypical Opinion Holders: What We can Learn from Experts and Analysts}, series = {Proceedings of the International Conference on Recent Advances in Natural Language Processing 2011, Hissar, Bulgaria, 12-14 September, 2011}, editor = {Galia Angelova and Kalina Bontcheva and Ruslan Mitkov and Nikolai Nikolov}, publisher = {Incoma Ltd.}, address = {Shoumen}, issn = {1313-8502}, url = {http://nbn-resolving.de/urn:nbn:de:bsz:mh39-84674}, pages = {282 -- 288}, year = {2019}, 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 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.}, language = {en} }