|
|
- 2017
网络大数据分析技术的心理学方法论思考
|
Abstract:
网络大数据已被成功应用于探索情绪心理学、人格心理学等诸多心理学研究议题。与以认知神经科学技术为例的现代研究方法，和以问卷法、行为实验法为例的传统研究方法相比，网络大数据分析在样本规模、数据客观性、时效性、生态学效度等方面均具有显著优势。具有浓厚学科交叉性质的认知神经科学技术和网络大数据分析技术，前者擅长于微观分析层面，后者擅长于分析宏观层面，且都是心理学适应现代化技术变迁、把握时代机遇的两大重要突破口。未来研究者可采取方法互补，数据驱动和理论驱动相结合等策略，从而更好地把握时代发展机遇。
Web big data has been successfully applied to explore various psychological issues, such as problems in emotion psychology, personality psychology. Compared with modern research methods, such as cognitive neuroscience technology, and traditional research methods, such as questionnaire and behavioral experiment, Network big data analysis has significant advantages in terms of sample size, data objectivity, timeliness, and ecological validity. Both cognitive neuroscience technology and Network big data analysis boast strong interdisciplinary nature, with the former specializing in micro-level analysis and the latter in macro-level analysis. Both of them are important breakthroughs of psychology adapting the change of modern technology, and seizing opportunities in the current era. Future study may consider the strategy of using complementary methods and combining both data-driven and theory-driven approaches in research design to make better use of the great opportunities in the information age
| [1] | 朱廷劭, 汪静莹, 赵楠, 等. 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, 36(4): 100-107. |
| [2] | 乐国安, 董颖红, 陈浩, 等. 在线文本情感分析技术及应用[J]. 心理科学进展, 2013, 21(10): 1711-1719. |
| [3] | 叶勇豪, 许燕, 朱一杰, 等. 网民对"人祸"事件的道德情绪特点——基于微博大数据研究[J]. 心理学报, 2016, 48(3): 290-304. |
| [4] | BOLLEN J, MAO H and ZENG X. Twitter mood predicts the stock market[J]. Journal of Computational Science, 2011, 2(1): 1-8. DOI:10.1016/j.jocs.2010.12.007 |
| [5] | WU Y, KOSINSKI M and STILLWELL D. Computer-based personality judgments are more accurate than those made by humans[J]. Proceedings of the National Academy of Sciences, 2015, 112(4): 1036-1040. DOI:10.1073/pnas.1418680112 |
| [6] | LI L, LI A, HAO B, et al. Predicting active users' personality based on micro-blogging behaviors[J]. Plos One, 2014, 9(1): e84997 DOI:10.1371/journal.pone.0084997 |
| [7] | EICHSTAEDT J C, SCHWARTZ H A, KERN M L, et al. Psychological language on Twitter predicts county-level heart disease mortality[J]. Psychological Science, 2015, 26(2): 159-169. DOI:10.1177/0956797614557867 |
| [8] | GOLDER S A and MACY M W. Diurnal and seasonal mood vary with work, sleep, and daylength across diverse cultures[J]. Science, 2011, 333(6051): 1878-1881. DOI:10.1126/science.1202775 |
| [9] | MITCHELL L, FRANK M R, HARRIS K D, et al. The geography of happiness: connecting twitter sentiment and expression, demographics, and objective characteristics of place[J]. Plos One, 2013, 8(5): e64417 DOI:10.1371/journal.pone.0064417 |
| [10] | RENTFROW P J, GOSLING S D and POTTER J. A theory of the emergence, persistence, and expression of geographic variation in psychological characteristics[J]. Perspectives on Psychological Science, 2008, 3(5): 339-369. DOI:10.1111/j.1745-6924.2008.00084.x |
| [11] | GON？ALVES B, PERRA N and VESPIGNANI A. Modeling users'activity on Twitter networks: validation of Dunbar'snumber[J]. Plos One, 2011, 6(8): e22656 DOI:10.1371/journal.pone.0022656 |
| [12] | 张卫东, 李其维. 认知神经科学对心理学的研究贡献―主要来自我国心理学界的重要研究工作述评[J]. 华东师范大学学报(教育科学版), 2007, 25(1): 46-55. |
| [13] | ARAL S and WALKER D. Identifying influential and susceptible members of social networks[J]. Science, 2012, 337(6092): 337-341. DOI:10.1126/science.1215842 |
| [14] | MACINNIS C C and HODSON G. Do American States with more religious or conservative populations search more for sexual content on Google?[J]. Archives of Sexual Behavior, 2015, 44(1): 137-147. DOI:10.1007/s10508-014-0361-8 |
| [15] | MAYER-SCH？NBERGER V, CUKIER K. Big data: a revolution that will transform how we live, work, and think[M]. Boston: Houghton Mifflin Harcourt, 2013. |
| [16] | SILVER N. The signal and the noise: why so many predictions fail-but some don't[M]. New York: Penguin, 2012. |
| [17] | 谢志刚. 大数据再掀经济学方法论之争[J]. 中国社会科学报, 2015 |
| [18] | 王天思. 大数据中的因果关系及其哲学内涵[J]. 中国社会科学, 2016(5): 22-42. |
| [19] | KRAMER A D, GUILLORY J E and HANCOCK J T. Experimental evidence of massive-scale emotional contagion through social networks[J]. Proceedings of the National Academy of Sciences, 2014, 111(24): 8788-8790. DOI:10.1073/pnas.1320040111 |
| [20] | 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, 60(5): 520-533. |
| [21] | YARKONI T. Psychoinformatics: new horizons at the interface of the psychological and computing sciences[J]. Current Directions in Psychological Science, 2012, 21(6): 391-397. DOI:10.1177/0963721412457362 |
| [22] | RENTFROW P J, JOKELA M and LAMB M E. regional personality differences in great britain[J]. Plos One, 2015, 10(3): e0122245 DOI:10.1371/journal.pone.0122245 |
| [23] | LU X and BRELSFORD C. Network structure and community evolution on Twitter: human behavior change in response to the 2011 Japanese earthquake and tsunami[J]. Scientific Reports, 2014, 4: 6773 |
| [24] | 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, 27(6): 647-657. |
| [25] | 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. |
| [26] | 陈浩, 乐国安, 李萌, 等. 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. |
| [27] | HEY T, TANSLEY S, TOLLE K M. The fourth paradigm: data-intensive scientific discovery[M]. Redmond, WA: Microsoft Research, 2009. |
| [28] | 薛婷, 陈浩, 赖凯声, 等. 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, 23(2): 325-337. |
| [29] | 董颖红, 陈浩, 赖凯声, 等. 微博客基本社会情绪的测量及效度检验[J]. 心理科学, 2015, 38(5): 521-528. |
| [30] | 赖凯声, 陈浩, 钱卫宁, 等. 微博情绪与中国股市:基于协整分析[J]. 系统科学与数学, 2014, 34(5): 565-575. |
| [31] | WOJCIK S P, HOVASAPIAN A, GRAHAM J, et al. Conservatives report, but liberals display, greater happiness[J]. Science, 2015, 347(6227): 1243-1246. DOI:10.1126/science.1260817 |
| [32] | 李其维. "认知革命"与"第二代认知科学"刍议[J]. 心理学报, 2008, 40(12): 1306-1327. |
| [33] | BOND R and MESSING S. Quantifying social media's political space: estimating ideology from publicly revealed preferences on Facebook[J]. American Political Science Review, 2015, 109(1): 62-78. DOI:10.1017/S0003055414000525 |
