Theme detection an exploration of opinion subjectivity

Work in opinion mining and classification often assumes the incoming documents to be opinionated. Opinion mining system makes false hits while attempting to compute polarity values for non-subjective or factual sentences or documents. It becomes imperative to decide whether a given document contains subjective information or not as well as to identify which portions of the document are subjective or factual. In this work a theme detection technique has been evolved for more generic domain independent subjectivity detection that classifies sentences with binary feature: opinionated or non-opinionated. Theme detection technique examines sentence level opinion and finally accumulates the opinion clues to reach the discourse level subjectivity. The subjectivity detection system has been evaluated on the multi perspective question answering (MPQA) corpus as well as on Bengali corpus. The system evaluation has shown the precision and recall values of 76.08 and 83.33 for English and 72.16 and 76.00 for Bengali respectively.