Structure and pattern of social tags for keyword selection behaviors

Hao Ren Ke, Ya Ning Chen

研究成果: 雜誌貢獻文章

8 引文 (Scopus)

摘要

This article identifies patterns and structures in the social tagging of scholarly articles in CiteULike. Using a dataset of 4,215 tags attributed to 1,600 scholarly articles from 15 library and information science journals, a network was built to understand users' information organization behavior. Social network analysis and the frequent-pattern tree method were used to discover the implicit patterns and structures embedded in social tags as well as in their use, based on 26 proposed tag categories. The pattern and structure of this network of social tags is characterized by power-law distribution, centrality, co-used tag categories, role sharing among tag categories, and similar roles of tag categories in associating distinct tag categories. Furthermore, researchers generated 21 path-based decision-making sub-trees providing valuable insights into user tagging behavior for information organization professionals. The limitations of this study and future research directions are discussed.

原文英語
頁(從 - 到)43-62
頁數20
期刊Scientometrics
92
發行號1
DOIs
出版狀態已發佈 - 2012 七月

指紋

Information science
Electric network analysis
Decision making
professional association
network analysis
information science
social network
decision making
organization
Law

ASJC Scopus subject areas

  • Social Sciences(all)
  • Computer Science Applications
  • Library and Information Sciences

引用此文

Structure and pattern of social tags for keyword selection behaviors. / Ke, Hao Ren; Chen, Ya Ning.

於: Scientometrics, 卷 92, 編號 1, 07.2012, p. 43-62.

研究成果: 雜誌貢獻文章

Ke, Hao Ren ; Chen, Ya Ning. / Structure and pattern of social tags for keyword selection behaviors. 於: Scientometrics. 2012 ; 卷 92, 編號 1. 頁 43-62.
@article{b7cfb1f3a7794a16b82750640a6926a6,
title = "Structure and pattern of social tags for keyword selection behaviors",
abstract = "This article identifies patterns and structures in the social tagging of scholarly articles in CiteULike. Using a dataset of 4,215 tags attributed to 1,600 scholarly articles from 15 library and information science journals, a network was built to understand users' information organization behavior. Social network analysis and the frequent-pattern tree method were used to discover the implicit patterns and structures embedded in social tags as well as in their use, based on 26 proposed tag categories. The pattern and structure of this network of social tags is characterized by power-law distribution, centrality, co-used tag categories, role sharing among tag categories, and similar roles of tag categories in associating distinct tag categories. Furthermore, researchers generated 21 path-based decision-making sub-trees providing valuable insights into user tagging behavior for information organization professionals. The limitations of this study and future research directions are discussed.",
keywords = "CiteULike, Frequent-pattern tree, Social network analysis, Social tags",
author = "Ke, {Hao Ren} and Chen, {Ya Ning}",
year = "2012",
month = "7",
doi = "10.1007/s11192-012-0718-5",
language = "English",
volume = "92",
pages = "43--62",
journal = "Scientometrics",
issn = "0138-9130",
publisher = "Springer Netherlands",
number = "1",

}

TY - JOUR

T1 - Structure and pattern of social tags for keyword selection behaviors

AU - Ke, Hao Ren

AU - Chen, Ya Ning

PY - 2012/7

Y1 - 2012/7

N2 - This article identifies patterns and structures in the social tagging of scholarly articles in CiteULike. Using a dataset of 4,215 tags attributed to 1,600 scholarly articles from 15 library and information science journals, a network was built to understand users' information organization behavior. Social network analysis and the frequent-pattern tree method were used to discover the implicit patterns and structures embedded in social tags as well as in their use, based on 26 proposed tag categories. The pattern and structure of this network of social tags is characterized by power-law distribution, centrality, co-used tag categories, role sharing among tag categories, and similar roles of tag categories in associating distinct tag categories. Furthermore, researchers generated 21 path-based decision-making sub-trees providing valuable insights into user tagging behavior for information organization professionals. The limitations of this study and future research directions are discussed.

AB - This article identifies patterns and structures in the social tagging of scholarly articles in CiteULike. Using a dataset of 4,215 tags attributed to 1,600 scholarly articles from 15 library and information science journals, a network was built to understand users' information organization behavior. Social network analysis and the frequent-pattern tree method were used to discover the implicit patterns and structures embedded in social tags as well as in their use, based on 26 proposed tag categories. The pattern and structure of this network of social tags is characterized by power-law distribution, centrality, co-used tag categories, role sharing among tag categories, and similar roles of tag categories in associating distinct tag categories. Furthermore, researchers generated 21 path-based decision-making sub-trees providing valuable insights into user tagging behavior for information organization professionals. The limitations of this study and future research directions are discussed.

KW - CiteULike

KW - Frequent-pattern tree

KW - Social network analysis

KW - Social tags

UR - http://www.scopus.com/inward/record.url?scp=84862659526&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84862659526&partnerID=8YFLogxK

U2 - 10.1007/s11192-012-0718-5

DO - 10.1007/s11192-012-0718-5

M3 - Article

AN - SCOPUS:84862659526

VL - 92

SP - 43

EP - 62

JO - Scientometrics

JF - Scientometrics

SN - 0138-9130

IS - 1

ER -