Paper: Do Neighbours Help? An Exploration of Graph-based Algorithms for Cross-domain Sentiment Classification

ACL ID D12-1060
Title Do Neighbours Help? An Exploration of Graph-based Algorithms for Cross-domain Sentiment Classification
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2012
Authors

This paper presents a comparative study of graph-based approaches for cross-domain sentiment classification. In particular, the paper analyses two existing methods: an optimisation problem and a ranking algorithm. We compare these graph-based methods with each other and with the other state-of- the-art approaches and conclude that graph domain representations offer a competitive solution to the domain adaptation problem. Analysis of the best parameters for graph- based algorithms reveals that there are no optimal values valid for all domain pairs and that these values are dependent on the characteristics of corresponding domains.