Web Science is an interdisciplinary arena. Motivated by the unforeseen scale and impact of the web, it addresses web-related research questions in a holistic manner, incorporating perspectives from a broad set of disciplines. There has been ongoing discussion about which disciplines are more or less present in the community, and about defining Web Science itself: there is, however, a dearth of empirical work in this area. This research note presents an early analysis of the presence of different disciplines in the Web Science community. To gain insight into this area, we applied Natural Language Processing and topic extraction to Web Science papers from 2009 to 2011. We compare the results to two current representations of Web Science: the 'Web Science butterfly' diagram and the Web Science Subject Categorization. We discuss the benefits of such an exploratory analysis, our early results, and steps for producing more robust results.