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.
For example, Park et al. REF defined "experience" as an activity or event an individual or a group has undergone, and classified experiencerevealing sentences in blogs based on features such as tense, mood, aspect, and modality.
Detecting Experiences from Weblogs
ACL
Computer Science