A random walk algorithm for automatic construction of domain-oriented sentiment lexicon

In recent years, many studies have been conducted to deal with automatic construction of domain-oriented sentiment lexicon. However, most of the attempts rely on only the relationship between sentiment words, failing to uncover the mutual relationship between the words and the documents, as well as ignoring the useful knowledge of some existed domains (or “old domain”). This paper proposes a random walk algorithm to construct domain-oriented sentiment lexicon by simultaneously utilizing sentiment words and documents from both old domain and target domain (or “new domain”). The approach simulates a random walk on the graphs that reflect four kinds of relationships (the relationship between words, the relationship from words to documents, the relationship between documents, the relationship from documents to words) between documents and words. Experimental results indicate that the proposed algorithm could dramatically improve the performance of automatic construction of domain-oriented sentiment lexicon.