Recent years have marked the beginning and expansion of the Social Web, in which people freely express and respond to opinion on a whole variety of topics. While the growing volume of subjective information available allows for better and more informed decisions of the users, the quantity of data to be analyzed imposed the development of specialized Natural Language Processing (NLP) systems that automatically detect subjectivity in text and subsequently extract, classify and summarize the opinions available on different topics. Although these research fields have been highly dynamic in the past years, dealing with subjectivity in text has proven to be a complex, interdisciplinary problem that remains far from being solved. Its challenges include the need to address the issue from different perspectives and at different levels, depending on the characteristics of the textual genre, the language(s) treated and the final application for which the analysis is done. Inspired by the objectives we aimed at in the first two editions of the Workshop on Computational Approaches to Subjectivity Analysis (WASSA 2010 and WASSA 2.011) and the final outcome, the purpose of the proposed 3rd edition of the Workshop on Computational Approaches to Subjectivity and Sentiment Analysis (WASSA 2012) is to create a framework for presenting and discussing the challenges related to subjectivity and sentiment analysis in NLP, from an interdisciplinary theoretical and practical perspective.