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

Fei Wang; Hanghang Tong; Phillip Yu; Charu Aggarwal

doi:10.1007/s10618-012-0271-0

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

Fei Wang, Hanghang Tong, Phillip Yu, Charu Aggarwal

Research output: Contribution to journal › Article › peer-review

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 language	English (US)
Pages (from-to)	415-419
Number of pages	5
Journal	Data Mining and Knowledge Discovery
Volume	25
Issue number	3
DOIs	https://doi.org/10.1007/s10618-012-0271-0
State	Published - Nov 2012
Externally published	Yes

ASJC Scopus subject areas

Information Systems
Computer Science Applications
Computer Networks and Communications

Online availability

10.1007/s10618-012-0271-0

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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",

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doi = "10.1007/s10618-012-0271-0",

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journal = "Data Mining and Knowledge Discovery",

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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.

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

Abstract

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