Volume 1, Issue 3, July 2013, Pages 167 - 173
Efficient Keyword-Related Data Collection in a Social Network with Weighted Seed Selection
- Changhyun Byun, Hyeoncheol Lee, Jongsung You, Yanggon Kim
- Corresponding Author
- Changhyun Byun
Available Online 15 January 2013.
- https://doi.org/10.2991/ijndc.2013.1.3.5How to use a DOI?
- social networks; twitter; seed analysis; initial nodes; crawling; presidential election 2012
- Data mining in a social network can yield interesting perspectives to understanding human behavior or detecting topics or communities. However, it is difficult to gather the data related to a specific topic due to the main characteristics of social media data: large, noisy, and dynamic. To collect the data related to a specific topic efficiently, we propose a new algorithm that selects better seeds with limited resources. Furthermore, we compare two data sets collected by the algorithm and existing approaches.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - JOUR AU - Changhyun Byun AU - Hyeoncheol Lee AU - Jongsung You AU - Yanggon Kim PY - 2013 DA - 2013/01 TI - Efficient Keyword-Related Data Collection in a Social Network with Weighted Seed Selection JO - International Journal of Networked and Distributed Computing SP - 167 EP - 173 VL - 1 IS - 3 SN - 2211-7946 UR - https://doi.org/10.2991/ijndc.2013.1.3.5 DO - https://doi.org/10.2991/ijndc.2013.1.3.5 ID - Byun2013 ER -