Social tags and citing documents are two forms of social annotations to scientific publications. These social annotations provide useful contextual and temporal information for the annotated work, which encapsulates the attention and interest of the annotators. In this work, we explore the use of social annotations for discovering trends in scientific publications. We propose a trend discovery process that employs trend estimation and trend selection and ranking for analyzing 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 annotated work.
social annotations, temporal profiles, emerging trends
Databases and Information Systems | Numerical Analysis and Scientific Computing
Data Management and Analytics
Workshop on Human-Computer Interaction and Information Retrieval 5th HCIR 2011, October 20
City or Country
Mountain View, CA
HU, Meiqun; LIM, Ee Peng; and JIANG, Jing.
Using Social Annotations for Trend Discovery in Scientific Publications. (2011). Workshop on Human-Computer Interaction and Information Retrieval 5th HCIR 2011, October 20. 1-4. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/1461
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.