Paper: Improving Citation Polarity Classification with Product Reviews

ACL ID P14-2008
Title Improving Citation Polarity Classification with Product Reviews
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2014
Authors

Recent work classifying citations in scien- tific literature has shown that it is possi- ble to improve classification results with extensive feature engineering. While this result confirms that citation classification is feasible, there are two drawbacks to this approach: (i) it requires a large anno- tated corpus for supervised classification, which in the case of scientific literature is quite expensive; and (ii) feature engi- neering that is too specific to one area of scientific literature may not be portable to other domains, even within scientific liter- ature. In this paper we address these two drawbacks. First, we frame citation clas- sification as a domain adaptation task and leverage the abundant labeled data avail- able in other domains. Then, to avoid over-engineering specific...