Detecting Experiences from Weblogs

Weblogs are a source of human activity knowledge comprising valuable information such as facts, opinions and personal experiences. In this paper, we propose a method for mining personal experiences from a large set of weblogs. We define experience as knowledge embedded in a collection of activities or events which an individual or group has actually undergone. Based on an observation that experience-revealing sentences have a certain linguistic style, we formulate the problem of detecting experience as a classification task using various features including tense, mood, aspect, modality, experiencer, and verb classes. We also present an activity verb lexicon construction method based on theories of lexical semantics. Our results demonstrate that the activity verb lexicon plays a pivotal role among selected features in the classification performance and shows that our proposed method outperforms the baseline significantly.

• Type: Journal
• Year: 2010
• Where: ACL
• Authors: Keun-Chan Park, Yoonjae Jeong, Sung-Hyon Myaeng
• Keywords: ACL 2010, Computational Linguistics, Experience, Personal Experiences, Verb Lexicon