Using social annotations for trend discovery in scientific publications
Meiqun Hu, Ee‐Peng Lim, Jing Jiang · 2011
Social tags and citing documents are two forms of social an-notations to scientific publications. These social annotations provide useful contextual and temporal information for the annotated work, which encapsulates the attention and in-terest of the annotators. In this work, we explore the use of social annotations for discovering trends in scientific publi-cations. We propose a trend discovery process that employs trend estimation and trend selection and ranking for ana-lyzing the emerging trends shown in the social annotation profiles. The proposed sigmoid trend estimator allows us to characterize and compare how much, when and how fast the trends emerge. To perform topic-specific trend analysis, we further adopt topic modeling on the annotation content to decapsulate the multitude of impact created by the anno-tated work.