论“大数据”、“云计算”时代背景下的心理学研究变革

doi:10.16088/j.issn.1001-6597.2017.01.015

Abstract

Abstract: The fast development of the Internet and information technology represented by big data and cloud computing is having an impact on the development and reform of research paradigm of social science, which leads the emergence of some new subdisciplines such as computational social science, computational social psychology, psychological informatics, etc. From the view of psychology, the era of “big data” and “cloud computing” not only provides possibilities for the reform of psychological research, but also promotes the rise and development of the fourth research paradigm, and the emergence and development of some new psychology disciplines. Its reform direction is: to weaken simple and strong causal hypotheses of psychology research; attach importance to the complex reference among multivariates; strengthen the equivalent statements on psychology concepts and their relations; and pay attention to the learning and application of emerging disciplines thoughts and methods. Consequently, psychological research should value the study of complex reference among multivariates, which needs to have the aid of technology and instruments of “big data” and “cloud computing” related, as well as the computional thoughts and methods of the emerging disciplines such as machine learning and artificial intelligence, etc; making efforts to integrate and set up the research paradigm of psychology and promoting its reform and development.

Key words: big data, cloud computing, psychological research, the fourth paradigm

CLC Number:

B84-0

XIAO Qian-guo, YU Jia-yuan. The Reform of Psychological Research in the Era of “Big Data” and “Cloud Computing”[J].Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2017, 53(1): 88-94.

References

[1] Collaboration O S.Estimating the reproducibility of psychological science[J]. Science, 2015, 349(6251): aac4716.
[2] Bohannon J.Many psychology papers fail replication test[J]. Science, 2015, 349(6251): 910-911.
[3] Lazer D, et al. Life in the network: the coming age of computational social science[J]. Science (New York, NY), 2009,323(5915): 721.
[4] Gosling S D,W Mason. Internet research in psychology[J]. Annual review of psychology, 2015, 66: 877-902.
[5] 朱廷劭,汪静莹,赵楠,刘晓倩. 论大数据时代的心理学研究变革[J].新疆师范大学学报(哲学社会科学版), 2015(4): 100-107.
[6] 邓仲华, 李志芳. 科学研究范式的演化——大数据时代的科学研究第四范式[J]. 情报资料工作, 2013(4):19-23.
[7] Mell P, T. Grance.The nist definition of cloud computing[J]. Communications of the Acm, 2011, 53(6): 50-50.
[8] Wang L, et al. Scientific Cloud Computing: Early Definition and Experience[G]. in IEEE International Conference on High PERFORMANCE Computing and Communications, 2008.
[9] 张建勋, 古志民,郑超. 云计算研究进展综述[J]. 计算机应用研究, 2010(2): 429-433.
[10] 白云娟,沈书生.云学习:云计算激发的学习理念[J]. 中国电化教育, 2011(8): 14-18.
[11] 李国杰.大数据研究的科学价值[J]. 中国计算机学会通讯, 2018(9): 8-15.
[12] 唐良树.“大数据”创新心理学研究范式[N].中国社会科学报, 2015-09-22(3).
[13] 乐国安,赖凯声.基于网络大数据的社会心理学研究进展[J]. 苏州大学学报(教育科学版), 2016, 4(1): 1-11.
[14] 贺威,刘伟榕, 大数据时代的科研革新[J]. 未来与发展, 2014(2): 2-5.
[15] 维克托·迈尔舍恩伯格. 大数据时代: 生活, 工作与思维的大变革[M]. 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[M]. Wired, 2008.
[17] 魏向清.语言研究“第四范式”之思[J]. 外语研究, 2014(4): 6-11.
[18] Chang, R.M., R.J. Kauffman, and Y.O. Kwon. Understanding the paradigm shift to computational social science in the presence of big data[J]. Decision Support Systems, 2014, 63(3): 67-80.
[19] Hey, A.J., S. Tansley, and K.M. Tolle. The fourth paradigm: data-intensive scientific discovery[J]. Microsoft Research Redmond, WA, 2009,1.
[20] 郝春宇.第四范式对社会科学研究的方法论意义[D].哈尔滨:哈尔滨工业大学人文与社会科学学院,2015.
[21] 黄晓艳,单晓钊.关于大数据——访中国工程院院士倪光南[J]. 高科技与产业化, 2013, 9(5): 40-45.
[22] 喻丰,彭凯平,郑先隽. 大数据背景下的心理学:中国心理学的学科体系重构及特征[J]. 科学通报, 2015(Z1): 520-533.
[23] 胡晓峰.大数据时代对建模仿真的挑战与思考[J]. 军事运筹与系统工程, 2013(4): 5-12.
[24] 陈浩,乐国安,李萌.计算社会科学: 社会科学与信息科学的共同机遇[J]. 西南大学学报 (社会科学版), 2013, 39(3): 87-93.
[25] Smith ER, F R Conrey.Agent-based modeling: A new approach for theory building in social psychology[J]. Personality and social psychology review, 2007, 11(1): 87-104.
[26] Yang J , S. Counts.Predicting the Speed, Scale, and Range of Information Diffusion in Twitter[J]. ICWSM, 2010,10: 355-358.
[27] 薛婷,陈浩,赖凯声. 心理信息学:网络信息时代下的心理学新发展[J]. 心理科学进展, 2015(2): 325-337.
[28] Mishra R, R Sharma. Big data: opportunities and challenges[J]. International Journal of Computer Science and Mobile Computing, 2015, 4(6): 27-35.
[29] Chen L. The topological approach to perceptual organization[J]. Visual Cognition, 2005, 12(4): 553-637.
[30] Levitin, Nuzzo, Ramsay. Introduction to functional data analysis[J]. Canadian Psychology, 2007,48(3): 135-155.
[31] 焦璨, 熊敏平,张敏强. 心理学研究数据类型与统计方法——谈函数型数据分析的引入[J]. 心理科学进展, 2010(8): 1314-1320.
[32] 陈晓锋, 殷瑞飞. 基于基函数展开的函数型数据聚类方法[J]. 统计与决策, 2009(19): 10-12.
[33] Escabias, M., A.M. Aguilera, and M.J. Valderrama. Principal component estimation of functional logistic regression: discussion of two different approaches[J]. Journal of Nonparametric Statistics, 2004,16(3-4): 365-384.
[34] Ramsay J O. Functional data analysis[M]. Wiley Online Library,2006.
[35] Hinton G E, R R Salakhutdinov. Reducing the dimensionality of data with neural networks[J]. Science, 2006, 313(5786): 504-507.
[36] 钟义信. 人工智能的突破与科学方法的创新[J]. 模式识别与人工智能, 2012(3): 456-461.
[37] 余嘉元. 基于遗传算法的模糊综合评价在心理测量中的应用[J]. 心理学报, 2009(10): 1015-1023.
[38] 钱锦昕,余嘉元. 运用基因表达式编程的自陈量表数据建模[J]. 心理学报, 2013(6): 11.
[39] 余嘉元. 粗糙集和神经网络在心理测量中的应用[J]. 心理学报, 2008,40(8): 939-946.
[40] Grønholdt L , A Martensen. Analysing customer satisfaction data: a comparison of regression and artificial neural networks[J]. International Journal of Market Research, 2005, 47(2): 121-130.
[41] 赫尔曼·哈肯. 高等协同学[M].北京: 科学出版社,1989.
[42] 王珍.协同学的哲学意义[J]. 贵州民族学院学报(哲学社会科学版), 1989(3): 25-31.
[43] 何建南. 哈肯大脑协同学及其认知意义[J]. 五邑大学学报(社会科学版), 2006, 8(2): 1-4.
[44] 李仲涟. 论心理的协同效应[J]. 湖南师范大学社会科学学报, 1987(5): 1-6.
[45] 李小平. 态度转变的协同学模型及其意义[J]. 心理科学, 1996(2): 113-114.
[46] 阮学云, 郑孝莲,黄秀峰. 协同学对大学生心理健康水平的理论探索[J]. 自然辩证法研究, 2013(7): 125-128.
[47] Shahar G, et al. An interactive‐synergetic approach to the assessment of personality vulnerability to depression: Illustration using the adolescent version of the Depressive Experiences Questionnaire[J]. Journal of Clinical Psychology, 2004, 60(6): 605-625.
[48] Dumas J E , P Lemay, J P Dauwalder. Dynamic analyses of mother–child interactions in functional and dysfunctional dyads: A synergetic approach[J]. Journal of Abnormal Child Psychology, 2001, 29(4): 317-329.
[49] 沈婷婷. 数据素养及其对科学数据管理的影响[J]. 图书馆论坛, 2015(1): 68-73.
[50] 申学易, 买晓琴,刘超. 基于互联网平台的大数据收集在社会认知研究中的应用[J]. 科学通报, 2015(11): 986-993.
[51] Killingsworth MA, D T Gilbert. A Wandering Mind Is an Unhappy Mind[J]. Science, 2010, 330(6006): 932.
[52] 靳宇倡, 秦启文,安俊秀. 网络群体心理趋势智能分析模型研究[J]. 计算机科学, 2010(6): 273-277.
[53] Oppenheimer D M , T Meyvis, N Davidenko. Instructional manipulation checks: Detecting satisficing to increase statistical power[J]. Journal of Experimental Social Psychology, 2009, 45(4): 867-872.
[54] Johnson J A. Web-based self-report personality scales[EB/OL]. http://dx.doi.org/10.1037/12076-010.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed

Comments

Recommended 10

[1]	. [J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2018, 1(1): 1 .
[2]	. [J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 0, (): 1 .
[3]	. [J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2018, 54(3): 1 -10 .
[4]	. [J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2018, 54(3): 11 -17 .
[5]	. [J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2018, 54(3): 18 -24 .
[6]	. [J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2018, 54(3): 25 -30 .
[7]	. [J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2018, 54(3): 31 -36 .
[8]	. [J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2018, 54(3): 37 -41 .
[9]	. [J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2018, 54(3): 42 -47 .
[10]	. [J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2018, 54(3): 48 -54 .

The Reform of Psychological Research in the Era of “Big Data” and “Cloud Computing”

PDF (PC)

Abstract

Cite this article

share this article

References

Related Articles 3

Metrics

Comments

Recommended 10

[1]	MA Liang. Civil Servants’ Information Technology Capacity and the Construction of Digital Government: Evidence from a Nationwide Survey of Urban China [J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2020, 56(2): 34-44.
[2]	Liu Jian-hua, Liu Xin-yi. The Risk of Big Data Technology and Its Precautionary Mechanism [J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2020, 56(1): 113-120.
[3]	LONG Guo-zhi, PAN Wu-yun. Big Data Thinking in Chinese Tone Research [J]. Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition), 2019, 55(4): 119-124.