Approaches to subjectivity and sentiment analysis often rely on manually or automatically constructed lexicons. Most such lexicons are compiled as lists of words, rather than word meanings (senses). However, many words have both subjective and objective senses, which is a major source of ambiguity in subjectivity and sentiment analysis.
The goal of this exploratory research project is to address this gap, by investigating novel methods for subjectivity sense labeling, and exploiting the results in sense-aware subjectivity analysis. Specifically, the project targets two research objectives. The first objective is to develop new methods for assigning subjectivity labels to word senses in a taxonomy. The second objective is to explore contextual subjectivity disambiguation techniques that will effectively make use of the word sense subjectivity annotations. By achieving these objectives, the project is expected to contribute to the understanding of the connections among subjectivity, word senses, and contextual subjectivity analysis, which will serve as a stepping stone for continued research efforts in this area.
The resources created in this project will be made available to the research community, which will help advance the state of the art in automatic sentiment and subjectivity analysis.
