Do Neighbours Help? An Exploration of Graph-based Algorithms for Cross-domain Sentiment Classification
Natalia Ponomareva, Mike A Thelwall · 2012
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-ofthe-art approaches and conclude that graph domain representations offer a competitive solution to the domain adaptation problem. Analysis of the best parameters for graphbased 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. 1