Demo Data from EDBT 2026 / reviewers in the wild / expert
Seok-Chul Baek
dblp:41/5988
· DBLP profile ↗
2ranked-venue papers
1as first author
0since 2021 · last 2015
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 1Databases, data management, data science and information retrieval · 1 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Databases, data mining, and information retrieval
1 paper |
Web and social media mining · 87% Data mining · 13% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Web and social media mining › online community analysis
community evolution |
0.1 | 1 | 2009 | Contents-Based Analysis of Community Formation and Evolution in Blogspace · ICDE 2009 |
Data mining › structured data mining › graph mining
community detection |
0.0 | 1 | 2009 | Contents-Based Analysis of Community Formation and Evolution in Blogspace · ICDE 2009 |
Methods — techniques the papers use, named apart from their topics
content similarity analysis · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | Analyzing Topological Characteristics of The Korean Blogosphere
Jiwoon Ha, Duck-Ho Bae, Minsoo Ryu, Sang-Wook Kim, Seok-Chul Baek, Byeong-Soo Jeong, Jin-Soo Cho |
J. Web Eng. | 5 |
| 2009 | Contents-Based Analysis of Community Formation and Evolution in BlogspaceabstractBlogspace is a primary example of online social networks. In blogspace, there are a number of communities, each of which consists of members having dense relationships with one another. In this paper, we address formation and evolution of blog communities. We first make two claims: (1) a high level of contents similarity of blogs increases the likelihood of their belonging to the same community in a blog network; (2) A high level of contents similarity of communities increases the possibility of their being merged into a bigger community in the future. We verify these claims by analyzing a large volume of real-world blog data of 2 millions bloggers through extensive experiments. Our results provide new insights towards subsequent research on formation and evolution of communities in a blog network. Seok-Chul Baek, Sukwon Kang, Hyung Noh, Sang-Wook Kim |
ICDE | 1 |