{"type":"ScholarlyArticle","title":"Balanced News Using Constrained Bandit-based Personalization","authors":[{"name":"Sayash Kapoor","slug":"sayash-kapoor","given":"Sayash","family":"Kapoor","affiliation":"† École Polytechnique Fédérale de Lausanne"},{"name":"Vijay Keswani","slug":"vijay-keswani","given":"Vijay","family":"Keswani","affiliation":"Indian Institute of Technology , Kanpur"},{"name":"Nisheeth K. Vishnoi","slug":"nisheeth-k-vishnoi","given":"Nisheeth K.","family":"Vishnoi","affiliation":"Indian Institute of Technology , Kanpur"},{"name":"L. Elisa Celis","slug":"l-elisa-celis","given":"L. Elisa","family":"Celis","affiliation":"Indian Institute of Technology , Kanpur"}],"abstract":"We present a prototype for a news search engine that presents balanced viewpoints across liberal and conservative articles with the goal of depolarizing content and allowing users to escape their filter bubble. The balancing is done according to flexible user-defined constraints, and leverages recent advances in constrained bandit optimization. We showcase our balanced news feed by displaying it side-by-side with the news feed produced by a traditional (polarized) feed.","doi":"10.24963/ijcai.2018/854","url":"https://ijcai.org/proceedings/2018/854","pdf":"https://ijcai.org/proceedings/2018/0854.pdf","markdown":"https://ijcai.org/proceedings/2018/854.md","bibtex":"https://ijcai.org/proceedings/2018/bibtex/854","volume":{"slug":"2018","title":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2018","url":"https://ijcai.org/proceedings/2018/","year":2018,"location":"Stockholm","dates":"13-19 July 2018","editors":"Jérôme Lang","isbn":"978-0-9992411-2-7","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2018"},"section":"Demos","track":"Demos","number":854,"pages":{"first":5835,"last":5837},"keywords":["Machine Learning: Online Learning","Multidisciplinary Topics and Applications: Personalization and User Modeling","Multidisciplinary Topics and Applications: Real-Time Systems","Multidisciplinary Topics and Applications: AI and Social Sciences"],"videos":[],"references":[{"position":1,"raw":"[Celis and Tekriwal, 2017] L. Elisa Celis and Siddhartha Tekriwal. What Do Users Want in Q&A Sites: Quality or Diversity? In International Conference on Computational Social Science (IC2S2), 2017.","title":"What Do Users Want in Q&A Sites: Quality or Diversity","authors":"L, Elisa Celis, Siddhartha Tekriwal","year":"2017","venue":"International Conference on Computational Social Science (IC2S2)","doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Celis et al., 2016] L. Elisa Celis, Amit Deshpande, Tarun Kathuria, and Nisheeth K. Vishnoi. How to be fair and diverse? Fairness, Accountability and Transparency in Machine Learning 2016, 2016.","title":"How to be fair and diverse? Fairness, Accountability and Transparency in Machine Learning","authors":"L Elisa Celis, Amit Deshpande, Tarun Kathuria, Nisheeth K Vishnoi","year":"2016","venue":null,"doi":null,"url":null,"internal_url":null},{"position":3,"raw":"[Celis et al., 2018a] L. Elisa Celis, Lingxiao Huang, and Nisheeth K. Vishnoi. Multiwinner voting with fairness constraints. In International Joint Conference on Artificial Intelligence, 2018.","title":"Multiwinner voting with fairness constraints","authors":"Celis","year":"2018","venue":"International Joint Conference on Artificial Intelligence","doi":null,"url":null,"internal_url":"/proceedings/2018/20"},{"position":4,"raw":"[Celis et al., 2018b] L. Elisa Celis, Sayash Kapoor, Farnood Salehi, and Nisheeth K. Vishnoi. An Algorithmic Frame- work to Control Bias in Bandit-based Personalization. ArXiv e-prints, February 2018.","title":"An Algorithmic Framework to Control Bias in Bandit-based Personalization","authors":"Celis","year":"2018","venue":null,"doi":null,"url":null,"internal_url":null},{"position":5,"raw":"[Celis et al., 2018c] L. Elisa Celis, Vijay Keswani, Damian Straszak, Amit Deshpande, Tarun Kathuria, and Nisheeth K. Vishnoi. Fair and diverse data sum- marization. In International Conference on Machine Learning, 2018.","title":"Fair and diverse data summarization","authors":"Celis","year":"2018","venue":"International Conference on Machine Learning","doi":null,"url":null,"internal_url":null},{"position":6,"raw":"[Celis et al., 2018d] L. Elisa Celis, Damian Straszak, and Nisheeth K. Vishnoi. Ranking with fairness constraints. In International Colloquium on Automata, Languages and Programming, 2018.","title":"Ranking with fairness constraints","authors":"Celis","year":"2018","venue":"International Colloquium on Automata, Languages and Programming","doi":null,"url":null,"internal_url":null},{"position":7,"raw":"[Datta et al., 2015] Amit Datta, Michael C. Tschantz, and Anupam Datta. Automated experiments on ad privacy set- tings. Proceedings on Privacy Enhancing Technologies, 2015(1):92-112, 2015.","title":"Automated experiments on ad privacy settings","authors":"Amit Datta, Michael C Tschantz, Anupam Datta","year":"2015","venue":"Proceedings on Privacy Enhancing Technologies","doi":null,"url":null,"internal_url":null},{"position":8,"raw":"[De Myttenaere et al., 2015] Arnaud De Myttenaere, Boris Golden, Bénédicte Le Grand, and Fabrice Rossi. Study of a bias in the offline evaluation of a recommendation al- gorithm. ArXiv e-prints, November 2015.","title":"Study of a bias in the offline evaluation of a recommendation algorithm","authors":"De Myttenaere","year":"2015","venue":null,"doi":null,"url":null,"internal_url":null},{"position":9,"raw":"[Dwork et al., 2012] Cynthia Dwork, Moritz Hardt, Toniann Pitassi, Omer Reingold, and Richard Zemel. Fairness through awareness. In Innovations in Theoretical Com- puter Science 2012, pages 214-226, 2012.","title":"Fairness through awareness","authors":"Cynthia Dwork, Moritz Hardt, Toniann Pitassi, Omer Reingold, Richard Zemel","year":"2012","venue":"Innovations in Theoretical Computer Science","doi":null,"url":null,"internal_url":null},{"position":10,"raw":"[Flaxman et al., 2016] Seth Flaxman, Sharad Goel, and Justin M. Rao. Filter bubbles, echo chambers, and online news consumption. Public Opinion Quarterly, 80(S1):298-320, 2016.","title":"Filter bubbles, echo chambers, and online news consumption","authors":"Seth Flaxman, Sharad Goel, Justin M Rao","year":"2016","venue":"Public Opinion Quarterly","doi":null,"url":null,"internal_url":null},{"position":11,"raw":"[H. Ribeiro et al., 2017] Manoel H. Ribeiro, Pedro H. Calais, Virgílio A. F. Almeida, and Wagner Meira, Jr. \"Ev- erything I Disagree With is #FakeNews\": Correlating Po- litical Polarization and Spread of Misinformation. ArXiv e-prints, June 2017.","title":"Correlating Political Polarization and Spread of Misinformation","authors":"H Manoel, Pedro H Ribeiro, Calais, A F Virgílio, Almeida, Wagner Meira","year":"2017","venue":null,"doi":null,"url":null,"internal_url":null},{"position":12,"raw":"[Matakos et al., 2017] Antonis Matakos, Evimaria Terzi, and Panayiotis Tsaparas. Measuring and moderating opinion polarization in social networks. Data Mining and Knowl- edge Discovery, 31(5):1480-1505, Sep 2017.","title":"Measuring and moderating opinion polarization in social networks","authors":"Antonis Matakos, Evimaria Terzi, Panayiotis Tsaparas","year":"2017","venue":"Data Mining and Knowledge Discovery","doi":null,"url":null,"internal_url":null},{"position":13,"raw":"[Yang and Stoyanovich, 2017] Ke Yang and Julia Stoy- anovich. Measuring fairness in ranked outputs. In Sci- entific and Statistical Database Management, pages 22:1- 22:6, 2017.","title":"Measuring fairness in ranked outputs","authors":"Ke Yang, Julia Stoyanovich","year":"2017","venue":"Scientific and Statistical Database Management","doi":null,"url":null,"internal_url":null},{"position":14,"raw":"[Zafar et al., 2017] Muhammad B. Zafar, Isabel Valera, Manuel Gomez-Rodriguez, and Krishna P. Gummadi. Fairness constraints: Mechanisms for fair classification. In International Conference on Artificial Intelligence and Statistics 2017, pages 962-970, 2017.","title":"Fairness constraints: Mechanisms for fair classification","authors":"Zafar","year":"2017","venue":"International Conference on Artificial Intelligence and Statistics 2017","doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}