Part 2. Data Analytics and Machine Learning

• Slide Download
• Short articles

- Hofman, J. M., Sharma, A., & Watts, D. J. (2017). Prediction and Explanation in Social Systems. Science, 355(6324), 486-488.

- Athey, S. (2017). Beyond Prediction: Using Big Data for Policy Problems. Science, 355(6324), 483-485.

• Brogaard, J., Engelberg, J., & Parsons, C. A. (2014). Networks and Productivity: Causal Evidence from Editor Rotations. Journal of Financial Economics, 111(1), 251-270.
• Bertsimas, D., Brynjolfsson, E., Reichman, S., & Silberholz, J. (2015). OR Forum—Tenure Analytics: Models for Predicting Research Impact. Operations Research, 63(6), 1246-1261. ("Moneyball for Professors," MIT Sloan Management Review. Dec 14, 2016)
• Optional

- Park, J., Kim, J., Pang, M. S., & Lee, B. (2017). Offender or Guardian? An Empirical Analysis of Ride-Sharing and Sexual Assault. KAIST Working Paper.

- Gerber, M. S. (2014). Predicting Crime Using Twitter and Kernel Density Estimation. Decision Support Systems, 61, 115-125.

• Slide Download
• Dhar, V., Geva, T., Oestreicher-Singer, G., & Sundararajan, A. (2014). Prediction in Economic Networks. Information Systems Research, 25(2), 264-284.
• Geva, T., Oestreicher-Singer, G., Efron, N., & Shimshoni, Y. (2017). Using Forum and Search Data for Sales Prediction of High-Involvement Projects. MIS Quarterly, 41(1), 65-82.
• Optional

- Goel, S., & Goldstein, D. G. (2014). Predicting Individual Behavior with Social Networks. Marketing Science, 33(1), 82-93.

- Shmueli, G., & Koppius, O. (2011). Predictive Analytics in Information Systems Research. MIS Quarterly, 35(3), 553-572.

• Slide Download
• See a TED video on machine learning

- How we're teaching computers to understand pictures (Fei-Fei Li, 2015)

• Jean, N., Burke, M., Xie, M., Davis, W. M., Lobell, D. B., & Ermon, S. (2016). Combining Satellite Imagery and Machine Learning to Predict Poverty. Science, 353(6301), 790-794.
• Shin, D., He, S., Lee, G., Whinston, A., Cetintas, S. & Lee, K. (2016). Content Complexity, Similarity, and Consistency in Social Media: A Deep Learning Approach. UT Austin Working Paper. Available at SSRN: https://ssrn.com/abstract=2830377
• Optional

- Lee, D. and Hosanagar, K. & Nair, H. (2017). Advertising Content and Consumer Engagement on Social Media: Evidence from Facebook. Management Science, forthcoming. Available at SSRN: https://ssrn.com/abstract=2290802

- Park, J., Kim, J., Cho, D., & Lee, B. (2017). Pitching with Style: The Role of Entrepreneur’s Speech in Crowdfunding Success. KAIST Working Paper.

- Zhang, S., Lee, D., Singh, P. V., & Srinivasan, K. (2017), How Much Is an Image Worth? Airbnb Property Demand Estimation Leveraging Large Scale Image Analytics. CMU Working Paper. Available at SSRN: https://ssrn.com/abstract=2976021

- Lin, Y. K., Chen, H., Brown, R. A., & Li, S. H. (2017). Healthcare Predictive Analytics for Risk Profiling in Chronic Care: A Bayesian Multitask Learning Approach. MIS Quarterly, 41(2), 473-495.

• Slide Download / Code
• Replication project for the following study:

- Kim, J. and Park, J. (2017). Does Facial Expression Matter Even Online? An Empirical Analysis of Creator’s Facial Expression of Emotion and Crowdfunding Success. KAIST Working Paper.

• Slide Download / Code