Identifying Thematic Variations in SDSS research.

Chaomei Chen (1) , Fidelia Ibekwe-Sanjuan (2) , Eric Sanjuan (3) , Michael Vogeley (4)

1 iSchool, University of Drexel, Philadelphia
2 ELICO - Equipe de recherche de Lyon en sciences de l'information et de la communication
3 LIA - Laboratoire Informatique d'Avignon
4 Department of Physics - Drexel University

The Sloan Digital Sky Survey (SDSS) is the largest ongoing sky survey. It regularly makes data releases to the astronomical community. From a macroscopic point of view, a profound question is: what is the role of SDSS data releases in the evolution of the relevant scientific fields? In this paper, we introduce an integrated approach by combining statistical, information-theoretical, and symbolic methods for text data analysis and show how this combined approach can distinguish thematic variations associated with the different data releases.

Mots clés: Text mining; topic detection; information visualization; thematic evolution.; thematic evolution

Domaines: Sciences de l'information et de la communication

Chaomei Chen, Fidelia Ibekwe-Sanjuan, Eric Sanjuan, Michael Vogeley. Identifying Thematic Variations in SDSS research.. 6th International Conference on Language Resources and Evaluation Conference (LREC-08), Mar 2008, Lyon, France. pp.319-330. ⟨hal-00635676⟩