Lexical Sense Labeling and Sentiment Potential Analysis Using Corpus-Based Dependency Graph

This paper describes a graph method for labeling word senses and identifying lexical sentiment potential by integrating the corpus-based syntactic-semantic dependency layer, semantic dictionaries. The method, implemented as ConGraCNet application on different languages corpora, projects function onto particular syntactical layer constructs seed lexeme with collocates of high conceptual similarity. is clustered into subgraphs that reveal polysemous nature in corpus. construction WordNet hypernym provides set synset labels generalize each cluster. By dictionaries, we introduce propagation methods analysis. Original dictionary values are integrated to compute node lexemes clusters, identify respect can be used resolve sparseness dictionaries enrich evaluation structures revealing relative specific proposed approach has complementary other NLP resources tasks, including disambiguation, domain relatedness, sense structure, metaphoricity, well cross- intra-cultural discourse variations prototypical conceptualization patterns knowledge representations.