Performing and Visualizing Temporal Analysis of Large Text Data Issued for Open Sources: Past and Future Methods

In this paper we first propose a state of the art on the methods for the visualization and for the interpretation of textual data, and in particular of scientific data. We then shortly present our contributions to this field in the form of original methods for the automatic classification of documents and easy interpretation of their content through characteristic keywords and classes created by our algorithms. In a second step, we focus our analysis on the data evolving over time. We detail our diachronic approach, especially suitable for the detection and for visualization of topic changes. This allows us to conclude with Diachronic’Explorer, our upcoming visualization tool for visual exploration of evolutionary data.