Guest editorial: Special issue on data mining technologies for computational social science

Fei Wang, Hanghang Tong, Phillip Yu, Charu Aggarwal

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

The article focuses on data mining technologies for computational social science. The emergence of online social network sites and web 2.0 applications generate a large volume of valuable data. This greatly stimulates the development of computational social science, which tries to solve the research problems in traditional social science with the help of computational technologies. In addition to novel computational models, it would also be interesting to see the application of data mining techniques in real social problems. With the burst of various online social network, people are also interested in mining the people emotions from those online data. There are many fundamental problems in social sciences, such as detecting underlying communities, analyzing the mechanism of a specific behavior (social activity) and discovering the evolutionary patterns in a community.

Original languageEnglish (US)
Pages (from-to)415-419
Number of pages5
JournalData Mining and Knowledge Discovery
Volume25
Issue number3
DOIs
StatePublished - Nov 2012
Externally publishedYes

Fingerprint

Social sciences
Data mining

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Computer Networks and Communications

Cite this

Guest editorial : Special issue on data mining technologies for computational social science. / Wang, Fei; Tong, Hanghang; Yu, Phillip; Aggarwal, Charu.

In: Data Mining and Knowledge Discovery, Vol. 25, No. 3, 11.2012, p. 415-419.

Research output: Contribution to journalArticle

@article{d61ec14c23604aa5af1a70010d8cdb63,
title = "Guest editorial: Special issue on data mining technologies for computational social science",
abstract = "The article focuses on data mining technologies for computational social science. The emergence of online social network sites and web 2.0 applications generate a large volume of valuable data. This greatly stimulates the development of computational social science, which tries to solve the research problems in traditional social science with the help of computational technologies. In addition to novel computational models, it would also be interesting to see the application of data mining techniques in real social problems. With the burst of various online social network, people are also interested in mining the people emotions from those online data. There are many fundamental problems in social sciences, such as detecting underlying communities, analyzing the mechanism of a specific behavior (social activity) and discovering the evolutionary patterns in a community.",
author = "Fei Wang and Hanghang Tong and Phillip Yu and Charu Aggarwal",
year = "2012",
month = "11",
doi = "10.1007/s10618-012-0271-0",
language = "English (US)",
volume = "25",
pages = "415--419",
journal = "Data Mining and Knowledge Discovery",
issn = "1384-5810",
publisher = "Springer Netherlands",
number = "3",

}

TY - JOUR

T1 - Guest editorial

T2 - Special issue on data mining technologies for computational social science

AU - Wang, Fei

AU - Tong, Hanghang

AU - Yu, Phillip

AU - Aggarwal, Charu

PY - 2012/11

Y1 - 2012/11

N2 - The article focuses on data mining technologies for computational social science. The emergence of online social network sites and web 2.0 applications generate a large volume of valuable data. This greatly stimulates the development of computational social science, which tries to solve the research problems in traditional social science with the help of computational technologies. In addition to novel computational models, it would also be interesting to see the application of data mining techniques in real social problems. With the burst of various online social network, people are also interested in mining the people emotions from those online data. There are many fundamental problems in social sciences, such as detecting underlying communities, analyzing the mechanism of a specific behavior (social activity) and discovering the evolutionary patterns in a community.

AB - The article focuses on data mining technologies for computational social science. The emergence of online social network sites and web 2.0 applications generate a large volume of valuable data. This greatly stimulates the development of computational social science, which tries to solve the research problems in traditional social science with the help of computational technologies. In addition to novel computational models, it would also be interesting to see the application of data mining techniques in real social problems. With the burst of various online social network, people are also interested in mining the people emotions from those online data. There are many fundamental problems in social sciences, such as detecting underlying communities, analyzing the mechanism of a specific behavior (social activity) and discovering the evolutionary patterns in a community.

UR - http://www.scopus.com/inward/record.url?scp=84865584637&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84865584637&partnerID=8YFLogxK

U2 - 10.1007/s10618-012-0271-0

DO - 10.1007/s10618-012-0271-0

M3 - Article

AN - SCOPUS:84865584637

VL - 25

SP - 415

EP - 419

JO - Data Mining and Knowledge Discovery

JF - Data Mining and Knowledge Discovery

SN - 1384-5810

IS - 3

ER -