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@article{ART001846816},
author={계용선 and Youngmi Yoon},
title={Follower classification system based on the similarity of Twitter node information},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2014},
volume={19},
number={1},
pages={111-118}

TY - JOUR
AU - 계용선
AU - Youngmi Yoon
TI - Follower classification system based on the similarity of Twitter node information
JO - Journal of The Korea Society of Computer and Information
PY - 2014
VL - 19
IS - 1
PB - The Korean Society Of Computer And Information
SP - 111
EP - 118
SN - 1598-849X
AB - Current friend recommendation system on Twitter primarily recommends the most influentialtwitter. However, this way of recommendation has drawbacks where it does not recommend theusers of which attributes of interests are similar to theirs. Since users want other users of whichattributes are similar, this study implements follower recommendation system based on thesimilarity of twitter node informations. The data in this study is from SNAP(Stanford NetworkAnalysis Platform), and it consists of twitter node information of which number of followers is over10,000 and twitter link information. We used the SNAP data as a training data, and generated a classifier which recommends and predicts the relation between followers. We evaluated theclassifier by 10-Fold Cross validation. Once two twitter node informations are given, our model canrecommend the relationship of the two twitters as one of following such as: FoFo(FollowerFollower), FoFr(Follower Friend), NC(Not Connected).
KW - Social Media Data;Twitter
DO -
UR -
ER -

계용선 and Youngmi Yoon. (2014). Follower classification system based on the similarity of Twitter node information. Journal of The Korea Society of Computer and Information, 19(1), 111-118.

계용선 and Youngmi Yoon. 2014, "Follower classification system based on the similarity of Twitter node information", Journal of The Korea Society of Computer and Information, vol.19, no.1 pp.111-118.

계용선, Youngmi Yoon "Follower classification system based on the similarity of Twitter node information" Journal of The Korea Society of Computer and Information 19.1 pp.111-118 (2014) : 111.

계용선, Youngmi Yoon. Follower classification system based on the similarity of Twitter node information. 2014; 19(1), 111-118.

계용선 and Youngmi Yoon. "Follower classification system based on the similarity of Twitter node information" Journal of The Korea Society of Computer and Information 19, no.1 (2014) : 111-118.

계용선; Youngmi Yoon. Follower classification system based on the similarity of Twitter node information. Journal of The Korea Society of Computer and Information, 19(1), 111-118.

계용선; Youngmi Yoon. Follower classification system based on the similarity of Twitter node information. Journal of The Korea Society of Computer and Information. 2014; 19(1) 111-118.

계용선, Youngmi Yoon. Follower classification system based on the similarity of Twitter node information. 2014; 19(1), 111-118.

계용선 and Youngmi Yoon. "Follower classification system based on the similarity of Twitter node information" Journal of The Korea Society of Computer and Information 19, no.1 (2014) : 111-118.