Paper: An Error Analysis of Relation Extraction in Social Media Documents

ACL ID P11-3012
Title An Error Analysis of Relation Extraction in Social Media Documents
Venue Annual Meeting of the Association of Computational Linguistics
Session Student Session
Year 2011
Authors

Relation extraction in documents allows the detection of how entities being discussed in a document are related to one another (e.g. part- of). This paper presents an analysis of a re- lation extraction system based on prior work but applied to the J.D. Power and Associates Sentiment Corpus to examine how the system works on documents from a range of social media. The results are examined on three dif- ferent subsets of the JDPA Corpus, showing that the system performs much worse on doc- uments from certain sources. The proposed explanation is that the features used are more appropriate to text with strong editorial stan- dards than the informal writing style of blogs.