Efficient Keyword-Related Data Collection in a Social Network with Weighted Seed Selection

DOI

10.2991/ijndc.2013.1.3.5How to use a DOI?

Keywords

social networks; twitter; seed analysis; initial nodes; crawling; presidential election 2012

Abstract

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.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Changhyun Byun
AU  - Hyeoncheol Lee
AU  - Jongsung You
AU  - Yanggon Kim
PY  - 2013
DA  - 2013/08/01
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  - 10.2991/ijndc.2013.1.3.5
ID  - Byun2013
ER  -