Interactions with big data analytics

被引:168
作者
Fisher, Danyel [1 ]
DeLine, Rob [1 ]
Czerwinski, Mary [1 ]
Drucker, Steven [1 ]
机构
[1] Microsoft Research, United States
关键词
Human computer interaction - User interfaces;
D O I
10.1145/2168931.2168943
中图分类号
学科分类号
摘要
Big data is useful for HCI researchers and user interface design. As one example, A/B testing is a standard practice in the usability community to help determine relative differences in user performance using different interfaces. This can help product teams discover large, real-world usability issues while supplementing laboratory techniques that tend to focus on smaller, more isolated problems. Other companies use the data more directly to modify their offerings. The online game company Zynga creates games and studies data on how its audience plays them in order to update the games immediately. The work creates a strong need to preserve institutional memory, both by tracking the origins of past decisions and by allowing repeatability across analyses. New data may well be constantly streaming in, so that the processing system needs to make decisions about which part of the stream to capture.
引用
收藏
页码:50 / 59
页数:9
相关论文
共 12 条
[1]  
Kohavi R., Longbotham R., Sommerfield D., Henne R.M., Controlled experiments on the web: Survey and practical guide, Data Mining and Knowledge Discovery, 18, 1, pp. 140-181, (2008)
[2]  
Fourney A., Mann R., Terry M., Characterizing the usability of interactive applications through query log analysis, Proc. of the 2011 Annual Conference on Human Factors in Computing Systems, pp. 1817-1826, (2011)
[3]  
Wingfield N., Virtual product, real profits: Players spend on Zynga's games, but quality turns some off, Wall Street Journal, (2011)
[4]  
Boyd D., Crawford K., Six provocations for big data, A Decade in Internet Time: Symposium on the Dynamics of the Internet and Society
[5]  
Woods D., Tableau Software's Pat Hanrahan on 'What Is A Data Scientist?', (2011)
[6]  
Simonson W., Alsbrooks W., A DBMS for the U. S. Bureau of the census, Proc. of the 1st International Conference on Very Large Data Bases, pp. 496-498, (1975)
[7]  
Shneiderman B., Extreme visualization: Squeezing a billion datapoints into a million pixels, Proc. of the ACM SIGMOD International Conference on Management of Data, pp. 3-12, (2008)
[8]  
Hellerstein J.M., Avnur R., Chou A., Olston C., Raman V., Roth T., Hidber C., Haas P., Interactive data analysis: The Control Project, IEEE Computer, 32, 8, (1999)
[9]  
Fisher D., Popov I., Drucker S., Schraefel M.C., Trust me, I'm partially right: Incremental visualization lets analysts explore large datsets faster, Proc. of CHI, (2012)
[10]  
Callahan S.P., Freire J., Santos E., Scheidegger C.E., Silva C.T., Vo H.T., VisTrails: Visualization meets data management, Proc. of ACM SIGMOD, (2006)