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A low-resources approach to Opinion Analysis: Machine Learning and Simple Approaches

In this paper I present a system for automatic opinion analysis built in a short time-frame using freely available open-source processing tools and lexical resources available from prior research. I use a simple feature-set that is largely language independent and a freely available machine-learning framework to model the subtasks as classification problems and report on my system’s performance. Additionally, I show that blind relevance feedback improves results sentencelevel relevance judgment. My system shows that it is possible to quickly build an opinion analysis system in a short period of time that can perform at an average level.