Research
Refereed Journal Publications
– “Who Is a Better Decision Maker? Data-Driven Expert Ranking Under Unobserved Quality”. 2021 Tomer Geva and Saar-Tsechansky. Production and Operations Management. 30(1):127-44.
– “Data-Driven Link Screening for Increasing Network Predictability.” 2021. Tomer Geva and Inbal Yahav”. IEEE Transactions on Knowledge and Data Engineering. 33(6): 2380 – 2391
– “More for less: adaptive labeling payments in online labor markets“. 2019. Tomer Geva, Maytal Saar-Tsechansky, Harel Lustiger. Data Mining and Knowledge Discovery.
– “Using Forum and Search Data for Sales Prediction of High-Involvement Products”. 2017. Tomer Geva, Gal Oestreicher-Singer, Niv Efron, Yair Shimshoni. MIS Quarterly (MISQ)
– “Crowd-Squared: Amplifying the Predictive Power of Search Trend Data”. 2016. Erik Brynjolfsson, Tomer Geva, Shachar Reichman. MIS Quarterly (MISQ)
– “Prediction in Economic Networks“. Vasant Dhar, Tomer Geva, Gal Oestreicher-Singer, Arun Sundararajan. 2014. Information Systems Research (ISR).
– “Empirical Evaluation of Automated Intraday Stock Recommendation System Incorporating both Market Data and Textual News“. 2014. Tomer Geva, Jacob Zahavi. Decision Support Systems (DSS).
Selected Work-In-Progress
– “A Machine Learning Framework Towards Transparency in Experts’ Decision Quality”. Joint work with Wanxue Dong and Maytal Saar-Tsechansky.
– “Quality Control for Crowd Workers and for Language Models: A Framework for Free-Text Response Evaluation with No Ground Truth”. Joint work with Anat Goldstein, Inbal Yahav and Shahar Meir.
– “Training Set Personalization for Minority Group Prediction”. Joint work with Moshe Unger
Selected Papers in Refereed Conference Proceedings
– “The Information Content of Multi Word Hashtags”. Zvi Ben Ami, Tomer Geva, Inbal Yahav. ICIS 2018
– “The Predictive Power of Engagement in Mobile Consumption”. Tomer Geva, Shachar Reichman, Iris Somech. ICIS 2017
– “Who’s A Good Decision Maker? Data-Driven Expert Worker Ranking under Unobservable Quality”. Tomer Geva, Maytal Saar-Tsechansky. ICIS 2016.
– “Using Crowd-Based Data Selection to Improve the Predictive Power of Search Trend Data”. Erik Brynjolfsson, Tomer Geva, Shachar Reichman. ICIS 2014.
– “Do Customers Speak Their Minds? Using Forums and Search for Predicting Sales”. Tomer Geva, Gal Oestreicher-Singer, Niv Efron, Yair Shimshoni. ICIS 2013.
– “Prediction in Economic Networks: Using the Implicit Gestalt in Product Graphs”. Vasant Dhar, Tomer Geva, Gal Oestreicher-Singer, Arun Sundararajan. ICIS 2012.
Selected Papers in Workshop Program
– “A Framework for Automated Worker Evaluation Based on Free-Text Responses with No Ground Truth”. Joint work with Anat Goldstein and Inbal Yahav – INFORMS Data Science Conference 2022
– “Training Set Personalization for Minority Group Prediction”. Tomer Geva and Inbal Yahav – WITS 2020
– “Training Set Personalization for Minority Group Prediction”. Tomer Geva and Inbal Yahav – INFORMS Data Science Conference 2020
– “On Data-Driven Inference of Experts’ Decision Qualities: New Problems & Algorithms”. Wanxue Dong, Maytal Saar-Tsechansky, Tomer Geva – WITS 2019
– “On Data-Driven Inference of Experts’ Decision Qualities: New Problems & Algorithms”. Wanxue Dong, Maytal Saar-Tsechansky, Tomer Geva – INFORMS Data Science Conference 2019
– “The Information Content of Multi-Word Hashtags”. Zvi Ben Ami, Tomer Geva, and Inbal Yahav – SCECR 2018
– “Data-Driven Network Tie Selection for Node Classification”. Tomer Geva, Inbal Yahav – INFORMS Data Science Conference 2017
– “Data-Driven Network Tie Selection for Node Classification”. Tomer Geva, Inbal Yahav – SCECR 2017
– “Data-Driven Network Tie Selection for Node Classification”. Tomer Geva, Inbal Yahav – WCBA 2017
– “Data-Driven Network Tie Selection for Node Classification”. Tomer Geva, Inbal Yahav. WCBA 2016.
– “Data-Driven Network Tie Selection for Node Classification”. Tomer Geva, Inbal Yahav. WITS 2016.
– “Who’s A Good Decision Maker? Data-Driven Expert Worker Ranking under Unobservable Quality”. Tomer Geva, Maytal Saar-Tsechansky. Statistical Challenges in eCommerce Research (SCECR) 2016.
– “More For Less: Adaptive Labeling Payment for Online Labor Markets”. Tomer Geva, Harel Lustiger, Maytal Saar-Tsechansky. WCBA 2016.
– “Cost-Effective Utilization of Online Workforce-Based Labeling”. Tomer Geva, Harel Lustiger, Maytal Saar-Tsechansky. Statistical Challenges in eCommerce Research (SCECR) 2015.
– “Crowd-Squared: Amplifying the Predictive Power of Large-Scale Crowd-Based Data”. Erik Brynjolfsson, Tomer Geva, Shachar Reichman. Conference of Information Systems and Technology (CIST) 2014.
– “Crowd-Squared: Amplifying the Predictive Power of Large-Scale Crowd-Based Data”. Erik Brynjolfsson, Tomer Geva, Shachar Reichman. Workshop on Information Systems and Economics (WISE) 2013.
– “Predicting Demand in Economic Networks”. Vasant Dhar, Tomer Geva, Gal Oestreicher-Singer, Arun Sundararajan. Workshop on Information in Networks (WIN) 2013.
– “Do Customers Speak Their Minds? Using Forums And Search for Predicting Sales”. Tomer Geva, Gal Oestreicher-Singer, Niv Efron, Yair Shimshoni. Statistical Challenges in eCommerce Research (SCECR) 2013.