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Sentiment analysis seeks to characterize opinionated or evaluative aspects of natural language text thus helping people to discover valuable information from large amounts of unstructured data . In this paper we explore a new methodology for sentiment analysis called proximity-based sentiment analysis. We take a different approach, by considering a new set of features based on word proximities in a written text. We propose three proximity-based features, namely, proximity distribution, mutual information between proximity types, and proximity patterns. We applied this approach to the analysis of movie reviews. Our experimental results show that proximity-based sentiment analysis is able to extract sentiments from a specific domain, with performance comparable to the state-of-the-art. To the best of our knowledge, this is the first attempt at focusing on only proximity based features as the primary features in sentiment analysis.