Sentiment and Belief: How to Think about, Represent, and Annotate Private States

Over the last ten years, there has been an explosion in interest in sentiment analysis, with many interesting and impressive results. For example, the first twenty publications on Google Scholar returned for the Query “sentiment analysis” all date from 2003 or later, and have a total citation count of 12,140. The total number of publications is in the thousands. Partly, this interest is driven by the immediate commercial applications of sentiment analysis. Sentiment is a “private state” (Wiebe, 1990). However, it is not the only private state that has received attention in the computational literature; others include belief and intention. In this tutorial, we propose to provide a deeper understanding of what a private state is. We will concentrate on sentiment and belief. We will provide background that will allow the tutorial participants to understand the notion of a private state as a cognitive phenomenon, which can be manifested linguistically in communication in various ways. We will explain the formalization in terms of a triple of state, source, and target. We will discuss how to model the source and the target. We will then explain in some detail the annotations that have been made. The issue of annotation is crucial for private states: while the MPQA corpus (Wiebe et al., 2005; Wilson, 2007) has been around for some time, most research using it does not make use of many of its features. We believe this is because the MPQA annotation is quite complex and requires a deeper understanding of the phenomenon of “private state”, which is what the annotation is getting at. Furthermore, there are currently several efforts underway of creating new versions of annotations, which we will also present. The larger goal of this tutorial is to allow the tutorial participants to gain a deeper understanding of the role of private states in human communication, and to encourage them to use this deeper understanding in their computational work. The immediate goal of this tutorial is to allow the participants to make more complete use of available annotated resources. We propose to achieve these goals by concentrating on annotated corpora, since this will allow participants to both understand the underlying content (achieving the larger goal) and the technical details of the annotations (achieving the immediate goal).