FATES 2019


FATES on the Web 2019
1st Workshop on Fairness, Accountability, Transparency, Ethics, and Society on the Web
In conjunction with The Web Conference 2019
May 14, 2019 San Francisco, CA, USA

About the Workshop

Can we build inclusive and representative machine-learning based-algorithms? Who is responsible for harm when algorithmic decision-making results in discriminatory outcomes? To whom should algorithms be transparent? What approaches to ethics might algorithms require? The FATES on the Web 2019 (Fairness, Accountability, Transparency, Ethics, and Society on the Web) is the first edition of a workshop to bring together researchers and enthusiasts concerned with the urgent challenges concerning algorithmic fairness and accountability, transparency, and ethics on data management and social interaction on the web. It will be co-located with The Web Conference 2019 (formerly known as WWW conference), to be hosted in San Francisco, California, celebrating this year the 30th anniversary of the Web.

The workshop will promote the discussion around these critical questions and join forces towards a Web that is truly inclusive and open, a Web for Good.

Topics and Themes 

The workshop encourages multidisciplinary submissions on, but not limited to: 

  • Fairness, accountability, transparency, and ethics in web search and (social) web mining
  • Algorithmic fairness and algorithmic bias, particularly on web data
  • Privacy-preserving and fairness-aware machine learning on the web
  • Fairness-aware recommender systems and diversity in recommendation
  • Transparency and ethics of web-scale data analysis
  • Transparency, fairness, and ethics of crowdsourcing
  • Ethics of opinion mining and opinion formation on the web
  • Hate speech in social media
  • Fake news, social bots, misinformation, and disinformation on social media
  • Credibility and reputation in social media
  • Ethics and legal audits on the use of sensitive data
  • Algorithmic fairness and bias for smart cities
  • Ethical aspects in mobility data analysis
  • Models for ensuring transparency and responsibility of government data
  • Transparency-aware algorithms for online civic engagement
  • Social sciences including sociology and political science and social web mining
  • Ethical-aware machine learning models for healthcare

All submissions will be peer reviewed and evaluated on the basis of originality, relevance, quality, and technical contribution. Submissions must present original work. Concurrent submissions are not allowed.


The papers accepted as full papers or short papers will be published jointly with The Web Conference proceedings. Papers accepted as discussion papers will not be published in the proceedings of The Web Conference.

Submission Guidelines

Authors can submit full papers (up to 10 pages in length), short papers (up to 6 pages in length), and discussion papers (up to 2 pages in length), written in English. The limit of pages includes the references. Papers must be submitted at https://easychair.org/conferences/?conf=fatesontheweb2019, in PDF according to the ACM format published in the ACM guidelines (www.acm.org/publications/proceedings-template), selecting the generic “sigconf” sample.

The PDF files must have all non-standard fonts embedded. PDF files must be double-blind. Submissions containing author identifying information are subject to rejection without review.

Important Dates

Paper submission deadline:

January 25

February 10, 2019
Paper acceptance notification: February 25, 2019
Paper camera-ready version: March 3, 2019
FATES on the Web 2019: May 14, 2019

Program Committee Co-Chairs and Organizers

Chiara Renso, ISTI/CNR, Italy
Daniel Sadoc Menasché, Federal University of Rio de Janeiro, Brazil
Jonice Oliveira, Federal University of Rio de Janeiro, Brazil
Lívia Ruback, Federal University of Rio de Janeiro, Brazil
Carlos Castillo, Universitat Pompeu Fabra, Barcelona
Jeanna Matthews, Clarkson University, USA


Program Committee


Aline Paes, UFF, Brazil
Anastasios Giovanidis, LIP6/Sorbonne Univ. (CNRS), France
Ana-Andreea Stoica, Columbia University, USA
Anna Monreale, University of Pisa, Italy 
Bettina Berendt, Univ. of Leuven, Belgium
Claudia Cappelli, PPGI/UFRJ, Brazil
Claudio Lucchese, Università Ca’ Foscari Venezia, Italy
Cristina Muntean, ISTI/CNR, Italy
Daniel Schwabe, PUC-Rio, Brazil 
Danilo Carvalho, Federal University of Rio de Janeiro
Elias Bareinboim, Purdue University, USA
Fabio Rangel, Federal University of Rio de Janeiro,
Fabrizio Silvestri, Facebook, London, UK
Giseli Rabello Lopes, Federal University of Rio de Janeiro, Brazil
Ida Mele, ISTI/CNR, Italy
Josep Domingo-Ferrer, Rovira i Virgili University, Catalonia
Karine Zeitouni, University of Versailles, France
Lily Hu, Harvard, USA
Marco Antonio Casanova, PUC-Rio, Brazil
Maria Luiza Machado Campos, Federal University of Rio de Janeiro, Brazil
Marília Guterres Ferreira, UDESC, Brazil
Michele Melchiori, University of Brescia, Italy
Raffaele Perego, ISTI/CNR, Italy
Regis Pires Magalhães, Federal University of Ceara, Brazil
Roberto Trani, ISTI/CNR, Italy
Vinicius Monteiro, UFPE, Brazil
Simone Diniz Junqueira Barbosa, PUC-Rio, Brazil
Stan Matwin, Dalhousie University, Canada

Invited Speaker

We are honored to announce that our invited speaker is Frauke Kreuter! Check the talk details below:

The Social Science of Privacy – Effects on Industry and Government Data Use

The sharing of data is at the core of many technology companies. Data sharing is also increasingly important for government decision-making, as stated by the Commission on Evidenced-Based Policymaking, which led to the Foundations for Evidence-Based Policymaking Act. However, in many instances, data used for decision-making is generated by people, and needs to be explicitly shared by the data subject with those wanting to use the data. The decision-making process behind sharing (private) information needs to be understood to assess (and circumvent) potential biases in the resulting data. When assessing bias in algorithmic decision-making, awareness of biases in the training data is essential. This presentation will review social science theories behind data sharing decision-making, highlight a series of experimental studies designed to affect sharing decisions, and present a framework design to detect sources of bias in various data sources.

Frauke Kreuter is a Professor in the Joint Program in Survey Methodology at the University of Maryland, Professor of Methods and Statistics at the University of Mannheim, and head of the statistical methods group at the German Institute for Employment Research in Nuremberg. Currently Frauke is a Visiting Scholar in Berkeley’s Simons Institute Program on Privacy. Frauke serves on several advisory boards for National Statistical Institutes around the world. She is a Gertrude Cox Award winner, which recognizes statisticians in early- to mid-career who have made significant breakthroughs in statistical practice, winner of the inaugural Links Lecture Award and elected fellow of the American Statistical Association. Additionally, she is co-founder of the Coleridge Initiative, and founder of the International Program in Survey and Data Science.


09.00 – 9.10 – Welcome from Organizers

09.10 – 09.50 Session 1: Privacy I

9.10 – 9.30 Privacy and Transparency within the 4IR: Two faces of the same coin (full)
Bianca Teixeira (PUC-Rio); Daniel Schwabe (PUC-Rio); Flavia Santoro (UERJ); Fernanda Baião (PUC-Rio); Maria Luiza Campos (UERJ); Letícia Verona (UERJ); Carlos Laufer (PUC-Rio); Simone Barbosa (PUC-Rio); Sérgio Lifschitz (PUC-Rio); Rosa Costa (UERJ)

9-30 – 9.40 Privacy-aware Linked Widgets (short) Javier D. Fernández (Vienna University of Economics and Business); Fajar J. Ekaputra (Vienna University of Technology); Peb Ruswono Aryan (Vienna University of Technology); Amr Azzam (Vienna University of Economics and Business); Elmar Kiesling (Vienna University of Technology)

9.40 – 9.50 Questions and debate

09.50 – 10.30 Session 2: Social Media I 

9.50 – 10.00 Trust and trustworthiness in social recommender systems (short)
Taha Hassan (Virginia Tech)

10.00 – 10.10 Black Hat Trolling, White Hat Trolling, and Hacking the Attention Landscape (short)
Jeanna Matthews (Clarkson University); Matt Goerzen (Data and Society)

10.10 – 10.20 Fairness in the social influence maximization problem (short)
Ana-Andreea Stoica (Columbia University); Augustin Chaintreau (Columbia University)

10.20 – 10.30 – Questions and debate

10.30 – 11.00 Coffee break 

11:00-12:00 – Keynote talk by Frauke Kreuter

The Social Science of Privacy – Effects on Industry and Government Data Use   – Frauke Kreuter

12:00-12:30 – Session 3: Bias I 

11.00 – 11.10 Can Location-Based Searches Create Exposure Bias? (discussion paper)
Gourab K Patro (Indian Institute of Technology Kharagpur); Ashmi Banerjee (Technical University of Munich); Niloy Ganguly (Indian Institute of Technology Kharagpur); Krishna P. Gummadi (MPI for Software Systems, Germany); Abhijnan Chakraborty (Max Planck Institute for Software Systems)

11.10 – 11.20 What’s in a Name? The Need for Scalable External Audit Infrastructure (discussion paper)
Aleksandra Korolova (University of Southern California); Kaushalkumar Shah (University of Southern California)

11.10 – 11.20 In Defense of Synthetic Data (discussion paper)
Luke Rodriguez (University of Washington); Bill Howe (University of Washington)

11.20 – 11.30 Questions and debate 

12.30 – 14.00 Lunch 

14:00-14:40  Session 4: Fairness 

14.00 – 14.10 Algorithms for Fair Team Formation in Online Labour Marketplaces (short)
Giorgio Barnabò (Sapienza University of Rome); Adriano Fazzone (Sapienza University of Rome); Chris Schwiegelshohn (Sapienza University of Rome); Stefano Leonardi (Sapienza University of Rome)

14-10 – 14.30 Quantifying the Impact of User Attention on Fair Group Representation in Ranked Lists (full)
Piotr Sapiezynski (Northeastern University); Wesley Zeng (Northeastern University); Ronald E Robertson (Northeastern University); Alan Mislove (Northeastern University); Christo Wilson (Northeastern University)

14.30 – 14.40 Questions and debate

14.40 – 15.30 Session 5: Privacy II 

14.40 – 14.50 Unsupervised Topic Extraction from Privacy Policies (short)
David Sarne (Bar-Ilan University); Jonathan Schler (Bar-Ilan University); Alon Singer (Bar-Ilan University); Ayelet Sela (Bar-Ilan University); Ittai Bar Siman Tov (Bar-Ilan University)

14.50 – 15.00 Collaborative Explanation of Deep Models with Limited Interaction for Trade Secret and Privacy Preservation (short)
Josep Domingo-Ferrer (Universitat Rovira i Virgili); Cristina Pérez (Universitat Rovira i Virgili); Alberto Blanco-Justicia (Universitat Rovira i Virgili)

15.00 – 15.10 Achieving Differential Privacy and Fairness in Logistic Regression (short)
Depeng Xu (University of Arkansas); Shuhan Yuan (University of Arkansas); Xintao Wu (University of Arkansas) 

15.10 – 15.20 On Preserving Sensitive Information of Multiple Aspect Trajectories In-House (short)
Spyros Giotakis (University of Piraeus); Nikos Pelekis (University of Piraeus)

15.20 – 15.30 Questions and debate 

15.30 – 16.00 Coffee break 

16:00-16:40 Session 6: Social Media II

16.00 – 16.10 Hegemony in Social Media and the effect of recommendations (short)
Ana-Andreea Stoica (Columbia University); Augustin Chaintreau (Columbia University)

16.10 – 16.30 Uncovering Social Media Bots: a Transparency-focused Approach (long)
Eric Ferreira Dos Santos (Federal University of Rio de Janeiro); Danilo Carvalho (Federal University of Rio de Janeiro); Lívia Ruback (Federal University of Rio de Janeiro); Jonice Oliveira (Federal University of Rio de Janeiro)

16.30 – 16.40 Questions and debate

16.40 – 17.30 Session 7:  Bias II

16.40 – 16.50 Managing Bias in AI (short)
Drew Roselli (ParallelM); Jeanna Matthews (Clarkson University); Nisha Talagala (ParallelM)

16.50 – 17.10 Nuanced Metrics for Measuring Unintended Bias with Real Data for Text Classification (full)
Daniel Borkan (Google); Lucas Dixon (Google); Jeffrey Sorensen (Google); Nithum Thain (Google); Lucy Vasserman (Google)

17.10 – 17.20 Empirical analysis of bias in voice based personal assistants (short)
Lanna Lima (Universidade de Fortaleza); Vasco Furtado (Universidade de Fortaleza); Elizabeth Furtado (Universidade de Fortaleza); Virgilio Almeida (Universidade Federal de Minas Gerais)

17.10 – 17.30 Questions and debate 

17.30 – 17.40 Closing

Web site graphics

Marcos Arrais, Federal University of Rio de Janeiro, Brazil

Any questions? Please contact fates19@isti.cnr.it