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7 results on '"Joseph Konstan"'

1. Six Human-Centered Artificial Intelligence Grand Challenges

Author

Ozlem Ozmen Garibay, Brent Winslow, Salvatore Andolina, Margherita Antona, Anja Bodenschatz, Constantinos Coursaris, Gregory Falco, Stephen M. Fiore, Ivan Garibay, Keri Grieman, John C. Havens, Marina Jirotka, Hernisa Kacorri, Waldemar Karwowski, Joe Kider, Joseph Konstan, Sean Koon, Monica Lopez-Gonzalez, Iliana Maifeld-Carucci, Sean McGregor, Gavriel Salvendy, Ben Shneiderman, Constantine Stephanidis, Christina Strobel, Carolyn Ten Holter, and Wei Xu

Subjects
Human-Computer Interaction, Human Factors and Ergonomics, ddc:004, Informatik [004], Computer Science Applications
Abstract

Widespread adoption of artificial intelligence (AI) technologies is substantially affecting the human condition in ways that are not yet well understood. Negative unintended consequences abound including the perpetuation and exacerbation of societal inequalities and divisions via algorithmic decision making. We present six grand challenges for the scientific community to create AI technologies that are human-centered, that is, ethical, fair, and enhance the human condition. These grand challenges are the result of an international collaboration across academia, industry and government and represent the consensus views of a group of 26 experts in the field of human-centered artificial intelligence (HCAI). In essence, these challenges advocate for a human-centered approach to AI that (1) is centered in human well-being, (2) is designed responsibly, (3) respects privacy, (4) follows human-centered design principles, (5) is subject to appropriate governance and oversight, and (6) interacts with individuals while respecting human’s cognitive capacities. We hope that these challenges and their associated research directions serve as a call for action to conduct research and development in AI that serves as a force multiplier towards more fair, equitable and sustainable societies.

Published
2023

2. Evolution of Experts in Question Answering Communities

Author

Aditya Pal, Shuo Chang, and Joseph Konstan

Abstract

Community Question Answering (CQA) services thrive as a result of a small number of highly active users, typically called experts, who provide a large number of high quality useful answers. Understanding the temporal dynamics and interactions between experts can present key insights into how community members evolve over time. In this paper, we present a temporal study of experts in CQA and analyze the changes in their behavioral patterns over time. Further, using unsupervised machine learning methods, we show the interesting evolution patterns that can help us distinguish experts from one another. Using supervised classification methods, we show that the models based on evolutionary data of users can be more effective at expert identification than the models that ignore evolution. We run our experiments on two large online CQA to show the generality of our proposed approach.

Published
2021
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3. User Modeling, Adaptation and Personalization : 19th International Conference, UMAP 2011, Girona, Spain, July 11-15, 2011

Author

Joseph Konstan, Ricardo Conejo, Jose L. Marzo, Nuria Oliver, Joseph Konstan, Ricardo Conejo, Jose L. Marzo, and Nuria Oliver

Subjects
User interfaces (Computer systems)--Congresses, Human-computer interaction--Congresses
Abstract

This book constitutes the proceedings of the third annual conference under the UMAP title, aptation, which resulted from the merger in 2009 of the successful biannual User Modeling (UM) and Adaptive Hypermedia (AH) conference series, held on Girona, Spain, in July 2011. The 27 long papers and 6 short papers presented together with15 doctoral consortium papers, 2 invited talks, and 3 industry panel papers were carefully reviewed and selected from 164 submissions. The tutorials and workshops were organized in topical sections on designing adaptive social applications, semantic adaptive social Web, and designing and evaluating new generation user modeling.

Published
2011

5. Social Comparisons and Contributions to Online Communities: A Field Experiment on MovieLens

Author

Yan Chen and Maxwell Harper and Joseph Konstan and Sherry Li, Chen, Yan, Harper, Maxwell, Konstan, Joseph, Li, Sherry, Yan Chen and Maxwell Harper and Joseph Konstan and Sherry Li, Chen, Yan, Harper, Maxwell, Konstan, Joseph, and Li, Sherry

Abstract

We explore the use of social comparison theory as a natural mechanism to increase contributions to an online movie recommendation community by investigating the effects of social information on user behavior in an online field experiment. We find that, after receiving behavioral information about the median user's total number of movie ratings, users below the median demonstrate a 530% increase in the number of monthly movie ratings, while those above the median decrease their monthly ratings by 62%. Movements from both ends converge towards the median, indicating conformity towards a newly-established social norm in a community where such a norm had been absent. Furthermore, the social information has a more dramatic effect on those below the median, suggesting an interaction between conformity and competitive preferences. When given outcome information about the average user's net benefit score from the system, consistent with social preference theory, users with net benefit scores above average contribute 94% of the new updates in the database. In both treatments, we find a highly significant Red Queen Effect.

Published
2007
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7. Word of Mouse : The Marketing Power of Collaborative Filtering

Author

John Riedl, Joseph Konstan, John Riedl, and Joseph Konstan

Subjects
Consumers--Research, Marketing research, Consumers--Research--Data processing, Marketing research--Data processing
Abstract

Through compelling case studies, Word of Mouse maps out a broad range of strategies that companies can employ to raise revenue, customer loyalty, and satisfaction.At the vanguard of the Internet revolution are two computer scientists from Minnesota who are pioneers of Collaborative Filtering (CF). CF is a technology that enables companies to understand their customers and in turn sell products, goods, and services with remarkable success. To test CF, John Riedl and Joseph Konstan built two Internet sites, MovieLens and GroupLens, that allowed users to customize their preferences for movies and news.The results were astounding -- MovieLens demonstrated amazing accuracy, almost ensuring that the recommendation would prove enjoyable. In'Word of Mouse,'the authors analyze dozens of companies from Best Buy to Amazon to TiVo -- and show what these companies are doing right -- and what they are doing wrong.

Published
2002

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