Information processing has become the backbone of modern society. So far, it has focused on objective content expressed in numbers and facts. However, human communication also contains sentiments, such as attitudes, emotions and social relations. Getting machines to process such information is one of the major next challenges for the progress of information technology.
We develop techniques for automatically analyzing sentiment in natural language texts, taking into account context and multi-faceted emotions. We use such analysis to better understand interactions in social networks, and to develop new forms of recommendation systems based on review texts.