Big Science and cross-disciplinary collaborations have reshaped the intellectual structure of research areas. A number of works have tried to uncover this hidden intellectual structure by analyzing citation contexts. However, none of them analyzed by document logical structures such as sections. The two major goals of this study are to find characteristics of authors who are highly cited section-wise and to identify the differences in section-wise author networks. This study uses 29,158 of research articles culled from the ACL Anthology, which hosts articles on computational linguistics and natural language processing. We find that the distribution of citations across sections is skewed and that a different set of highly cited authors share distinct academic characteristics, according to their citation locations. Furthermore, the author networks based on citation context similarity reveal that the intellectual structure of a domain differs across different sections.
|Number of pages||14|
|Journal||Journal of the Association for Information Science and Technology|
|Publication status||Published - 2017 Aug 1|
Bibliographical noteFunding Information:
This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2015S1A3A2046711).
© 2017 ASIS&T
All Science Journal Classification (ASJC) codes
- Information Systems
- Computer Networks and Communications
- Information Systems and Management
- Library and Information Sciences