Improving DBLP Efficiency through Social Media Mining
Faryal Shamsi, Irum Sindhu
International Journal of Web Applications, Vol. 13, No. 4, 2021.
DOI: https://doi.org/10.6025/ijwa/2021/13/4/97-104
Link: https://www.dline.info/ijwa/fulltext/v13n4/ijwav13n4_1.pdf
Abstract:
Social media mining provides a system to extract meaningful patterns from rapidly growing social networks. DBLP is a well-known dataset of the computer science bibliography, which gathers the computer science research community under single umbrella. The dataset provides millions of records, which include research publications journals, conferences and author information. This study intends to understand the social network of authors, by utilizing the records available in DBLP. This will help in recognizing the same author appearing with variation in names. For example, John F. Kennedy may appear in different variations, like â€“ John Fitzgerald Kennedy, John Kennedy, J.F Kennedy or even JFK. Because of these variations DBLP is unable to produce correct information about the research index and publications of an author. Understanding the social network of John F. Kennedy will help us in recognizing that, these different names are referring to the same author thus improving overall efficiency of DBLP.