Concept of Data from the Perspective of Computational Social Sciences

doi:10.13438/j.cnki.jdxb.2018.02.003

Abstract

Abstract: The advent of a data-intensive era marked by big data has providedabundant research materials and new data processing technologies for the empirical research in social sciences,and the computational social sciences have won a major opportunity for development.However,the current confusion and generalization of the concept of big data have led to many cognitive deviations in the data-intensive knowledge discovery and the theories and methods of social sciences.This paper clarifies the definition of big data from the perspective of social sciences by analyzing the nature and characteristics of big data,a new generation of information technology system represented by IoT,non-relational database,cloud computing and artificial intelligence which are closely related to big data,and the relationship between the two.On this basis,according to the status of real data and the level of data processing technology,it illustrates the advantages and limitations of the current data-driven knowledge discovery,the knowledge discovery of bi-direction-driven theoretical data,and the difficulties and breakthrough directions in computational social sciences research.

Key words: big data, computational social sciences, data-intensive era

LUO Jun,LI Fengxiang. Concept of Data from the Perspective of Computational Social Sciences[J]. Journal of Jishou University（Social Sciences）, DOI: 10.13438/j.cnki.jdxb.2018.02.003.

References

[1] Gandomi,A.,Haider,M.Beyond the hype:big data concepts,methods,and analytics.International Journal of Information Management,2015,35(2). [2] Bankes S,Lempert R,Popper S.Making computational social science effective:epistemology,methodology,and technology [J].Social Science Computer Review,2002,20(4). [3] Kuznar L A.High Fidelity Computational Social Science in Anthropology:Prospects for Developing a Comparative Framework[J].Social Science Computer Review,2006,24(1). [4] 阿尔文·托夫勒.未来的冲击[M].孟广均，译.北京：新华出版社，1996. [5] 阿尔文·托夫勒.第三次浪潮[M].朱志焱，等译.北京：新华出版社，1996. [6] Laney,D.3D data management:Controlling data volume,velocity and variety[R].META Group Research Note,2001,issue February. [7] Hey T,Tansley S,and Tolle K,(eds).Jim Gray on eScience:A Transformed Scientific Method[M]//Tony Hey,Stewart Tansley,and Kristin Tolle (eds).The Fourth Paradigm:Data-Intensive Scientific Discovery.Washington:Microsoft Research,2009. [8] Listed N.Community cleverness required.[J].Nature,2008,455(7 209). [9] Frankel F,Reid R.Big data:Distilling meaning from data[J].Nature,2008,455(7 209). [10] Lazer,D.,Pentland,A.,et al.Social science.Computational social science [J].Science,2009,323(5 915). [11] Gantz J,Reinsel,D.The Digital Universe in 2020:big data,bigger digital shadows,and biggest growth in the far east[R].In:IDC iView:IDC Analyze the Future,2012. [12] 李国杰,程学旗.大数据研究:未来科技及经济社会发展的重大战略领域——大数据的研究现状与科学思考[J].中国科学院院刊,2012(6). [13] Brown B,Bughin J,Byer AH,et al.Big Data:The Next Frontier For Innovation,Competition,And Productivity[EB/OL].[2017-05-26].https://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/big-data-the-next-frontier-for-innovation,2011-05. [14] Gartner.Gartner IT Glossary - Big Data[EB/OL].[2017-05-26].https://www.gartner.com/it-glossary/big-data,2013-09. [15] 维克托·迈尔-舍恩伯格，肯尼思·库克耶.大数据时代:生活、工作与思维的大变革[M].盛杨燕，周涛，译.杭州：浙江人民出版社，2013. [16] Anderson,C.The end of theory:The data deluge makes the scientific method obsolete.Wired magazine,2008(7). [17] 钟瑛,张恒山.大数据的缘起、冲击及其应对[J].现代传播（中国传媒大学学报）,2013(7). [18] Mauro A D,Greco M,Grimaldi M.What is big data? A consensual definition and a review of key research topics[C].AIP conference proceedings,2015,1644(1). [19] 中国信息通信研究院.大数据白皮书（2014）[R/OL].http://www.caict.ac.cn/kxyj/qwfb/bps/201512/t20151211_2146684.htm,201512. [20] 邬贺铨.大数据思维[J].科学与社会,2014(1). [21] 罗俊,罗教讲.数据密集型知识发现的边界与陷阱——以美国大选预测为例[J].学术论坛,2017(3). [22] Mason W,Vaughan J W,Wallach H.Computational social science and social computing[J].Machine Learning,2014,95(3).