Entity/event-level sentiment detection and inference

Abstract

Most of the work in sentiment analysis and opinion mining focuses on extracting explicit sentiments. Opinions may be expressed implicitly via inference rules over explicit sentiments. In this thesis, we incorporate the inference rules as constraints in joint prediction models, to develop an entity/event-level sentiment analysis system which aims at detecting both explicit and implicit sentiments expressed among entities and events in the text, especially focusing on but not limited to sentiments toward events that positively or negatively affect entities (+/-effect events).