Research

Google Scholar profile


Panos’ research program studies how information systems and technological artifacts affect the user behavior and transform business and society. His research focuses on personalization, mobile and social commerce, and online education. Much of this research is grounded in big data employing data science and machine-learning techniques to leverage the abundance of unstructured data in social media, while combining these approaches with more conventional econometric and other quantitative methods as well as experimental research designs.

Journal Publications

view download BibTeX Google Scholar Panagiotis Adamopoulos, Anindya Ghose, Vilma Todri: Estimating the Impact of User Personality Traits on Word-of-Mouth: Text-mining Microblogging Platforms. Forthcoming at Information Systems Research (ISR)

view download BibTeX Google Scholar Panagiotis Adamopoulos, Alexander Tuzhilin: On Unexpectedness in Recommender Systems: Or How to Better Expect the Unexpected. ACM Transactions on Intelligent Systems and Technology (ACM TIST) [2014 Impact Factor: 9.39 - Featured Article]

Under Review

view Panagiotis Adamopoulos, Anindya Ghose, Alexander Tuzhilin: The Business Value of Recommendations in a Mobile Application: Combining Deep Learning with Econometrics.

view Panagiotis Adamopoulos, Anindya Ghose, Vilma Todri: The Business Impact of the Internet of Things: Evidence from an Online Retailer.

In Proceedings

view download BibTeX Google Scholar Panagiotis Adamopoulos, Vilma Todri: The Effectiveness of Marketing Strategies in Social Media: Evidence from Promotional Events. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2015) [INFORMS social media analytics best paper award finalist]

view download BibTeX Google Scholar Panagiotis Adamopoulos, Alexander Tuzhilin: The Business Value of Recommendations: A Privacy-Preserving Econometric Analysis. International Conference on Information Systems (ICIS 2015)

view download BibTeX Google Scholar Panagiotis Adamopoulos, Alexander Tuzhilin, Peter Mountanos: Measuring the Concentration Reinforcement Bias of Recommender Systems. ACM Conference on Recommender Systems (RecSys 2015)

view download BibTeX Google Scholar Panagiotis Adamopoulos, Vilma Todri: Personality-Based Recommendations: Evidence from Amazon.com. ACM Conference on Recommender Systems (RecSys 2015)

view download BibTeX Google Scholar Vilma Todri, Panagiotis Adamopoulos: Social Commerce: An Empirical Examination of the Antecedents and Consequences of Commerce in Social Network Platforms. International Conference on Information Systems (ICIS 2014)

view download BibTeX Google Scholar Panagiotis Adamopoulos, Vilma Todri: Social Commerce Analytics: The Effectiveness of Promotional Events on Brand Fan Base in Social Media. International Conference on Information Systems (ICIS 2014)

view download BibTeX Google Scholar Panagiotis Adamopoulos, Alexander Tuzhilin: On Over-Specialization and Concentration Bias of Recommendations: Probabilistic Neighborhood Selection in Collaborative Filtering Systems. ACM Conference on Recommender Systems (RecSys 2014) [Video] [nominated for best paper award]

view download BibTeX Google Scholar Panagiotis Adamopoulos, Alexander Tuzhilin: Estimating the Value of Multi-Dimensional Data Sets in Context-based Recommender Systems. ACM Conference on Recommender Systems (RecSys 2014) [Data]

view download BibTeX Google Scholar Panagiotis Adamopoulos, Alejandro BellogĂ­n, Pablo Castells, Paolo Cremonesi, and Harald Steck: Recommender Systems Evaluation: Dimensions and Design. ACM Conference on Recommender Systems (RecSys 2014)

view download BibTeX Google Scholar Panagiotis Adamopoulos: On Discovering non-Obvious Recommendations: Using Unexpectedness and Neighborhood Selection Methods in Collaborative Filtering Systems. ACM Conference on Web Search and Data Mining (WSDM 2014): 655-660

view download BibTeX Google Scholar Panagiotis Adamopoulos: Novel Perspectives in Collaborative Filtering Recommender Systems. International World Wide Web Conference (WWW 2014)

view download BibTeX Google Scholar Panagiotis Adamopoulos: What Makes a Great MOOC? An Interdisciplinary Analysis of Student Retention in Online Courses. International Conference on Information Systems (ICIS 2013) [The most heavily-cited paper from the ICIS 2013 proceedings (as of September 22nd, 2015), according to Google Scholar]

view download BibTeX Google Scholar Panagiotis Adamopoulos, Alexander Tuzhilin: Recommendation Opportunities: Improving Item Prediction Using Weighted Percentile Methods in Collaborative Filtering Systems. ACM Conference on Recommender Systems (RecSys 2013): 351-354

view download BibTeX Google Scholar Panagiotis Adamopoulos: Beyond Rating Prediction Accuracy: On New Perspectives in Recommender Systems. ACM Conference on Recommender Systems (RecSys 2013): 459-462

view download BibTeX Google Scholar Panagiotis Adamopoulos, Alexander Tuzhilin: On Unexpectedness in Recommender Systems: Or How to Expect the Unexpected. Workshop on Novelty and Diversity in Recommender Systems (DiveRS 2011), at the ACM Conference on Recommender Systems (RecSys 2011): 21-28

Doctoral Dissertation

Dissertation Committee: Gediminas Adomavicius, Daria Dzyabura, Anindya Ghose, Srikanth Jagabathula, Foster Provost, Alexander Tuzhilin (Chairperson), Akhmed Umyarov
download BibTeX Google Scholar Thesis: Unexpectedness and Non-Obviousness in Recommendation Technologies and Their Impact on Consumer Decision Making

Software and Data Sets

ConcertTweets: A Multi-Dimensional Data Set for Recommender Systems Research