Future machines will connect with users on an emotional level in addition to performing complex computations (Norman 2004). In this article, we present a system that adds an emotional dimension to an activity that Internet users engage in frequently, search. ESSE, which stands for Emotional State Search Engine, is a web search engine that goes beyond facilitating a user's exploration of the web by topic, as search engines such as Google or Yahoo! afford. Rather, it enables the user to browse their topically relevant search results by mood, providing the user with a unique perspective on the topic at hand. Consider a user wishing to read opinions about the new president of the United States. Typing "President Obama" into a Google search box will return (among other results), a few recent news stories about Obama, the Whitehouse's website, as well as a wikipedia article about him. Typing "President Obama" into a Google Blog Search box will bring the user a bit closer to their goal in that all of the results are indeed blogs (typically opinions) about Obama. However, where blog search engines fall short is in providing users with a way to navigate and digest the vastness of the blogosphere, the incredible number of results for the query "President Obama" (approximately 17335307 as of 2/24/09) (Google Blog Search 2009). ESSE provides another dimension by which users can take in the vastness of the web or the blogosphere. This article outlines the contributions of ESSE including a new approach to mood classification.