title: Incorporating conditional random fields and active learning to improve sentiment identification.
abstract: Many machine learning, statistical, and computational linguistic methods have been developed to identify sentiment of sentences in documents, yielding promising results. However, most of state-of-the-art methods focus on individual sentences and ignore the impact of context on the meaning of a sentence. In this paper, we propose a method based on conditional random fields to incorporate sentence structure and context information in addition to syntactic information for improving sentiment identification. We also investigate how human interaction affects the accuracy of sentiment labeling using limited training data. We propose and evaluate two different active learning strategies for labeling sentiment data. Our experiments with the proposed approach demonstrate a 5%-15% improvement in accuracy on Amazon customer reviews compared to existing supervised learning and rule-based methods.
authors.affiliation: University of Illinois at Chicago, Chicago, IL, USA. Electronic address: kzhang6@uic.edu.
authors.forename: Kunpeng
authors.initials: K
authors.lastname: Zhang
authors.affiliation: Northwestern University, Evanston, IL, USA. Electronic address: yushengxie2011@u.northwestern.edu.
authors.forename: Yusheng
authors.initials: Y
authors.lastname: Xie
authors.affiliation: Northwestern University, Evanston, IL, USA. Electronic address: yya518@eecs.northwestern.edu.
authors.forename: Yi
authors.initials: Y
authors.lastname: Yang
authors.affiliation: Cloud Research Lab, Samsung Research America, San Jose, CA, USA. Electronic address: a.sun@samsung.com.
authors.forename: Aaron
authors.initials: A
authors.lastname: Sun
authors.affiliation: University of Science and Technology of China, Hefei, China. Electronic address: hcliu@ustc.edu.cn.
authors.forename: Hengchang
authors.initials: H
authors.lastname: Liu
authors.affiliation: Northwestern University, Evanston, IL, USA. Electronic address: choudhar@eecs.northwestern.edu.
authors.forename: Alok
authors.initials: A
authors.lastname: Choudhary
mesh_terms: D001185:Artificial Intelligence; D006801:Humans; D008037:Linguistics; D010364:Pattern Recognition, Visual; D018794:Problem-Based Learning / Q000379:methods*
keywords: Active learning; Conditional random fields; Customer reviews; Sentiment analysis