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Bias and Social Aspects in Search and Recommendation

First International Workshop, BIAS 2020, Lisbon, Portugal, April 14, Proceedings

  • Conference proceedings
  • © 2020

Overview

Editors:
  1. Ludovico Boratto

    1. Eurecat - Centre Tecnològic de Catalunya, Barcelona, Spain

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  2. Stefano Faralli

    1. Unitelma Sapienza University of Rome, Rome, Italy

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  3. Mirko Marras

    1. University of Cagliari, Cagliari, Italy

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  4. Giovanni Stilo

    1. University of L’Aquila, L’Aquila, Italy

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Part of the book series: Communications in Computer and Information Science (CCIS, volume 1245)

Included in the following conference series:

Conference proceedings info: BIAS 2020.

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Table of contents (18 papers)

  1. Front Matter

    Pages i-x
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  2. Facets of Fairness in Search and Recommendation

    • Sahil Verma, Ruoyuan Gao, Chirag Shah
    Pages 1-11

  3. Mitigating Gender Bias in Machine Learning Data Sets

    • Susan Leavy, Gerardine Meaney, Karen Wade, Derek Greene
    Pages 12-26

  4. Why Do We Need to Be Bots? What Prevents Society from Detecting Biases in Recommendation Systems

    • Tobias D. Krafft, Marc P. Hauer, Katharina A. Zweig
    Pages 27-34

  5. Effect of Debiasing on Information Retrieval

    • Emma J. Gerritse, Arjen P. de Vries
    Pages 35-42

  6. Matchmaking Under Fairness Constraints: A Speed Dating Case Study

    • Dimitris Paraschakis, Bengt J. Nilsson
    Pages 43-57

  7. Recommendation Filtering à la carte for Intelligent Tutoring Systems

    • Wesley Silva, Marcos Spalenza, Jean-Rémi Bourguet, Elias de Oliveira
    Pages 58-65

  8. bias goggles: Exploring the Bias of Web Domains Through the Eyes of Users

    • Giannis Konstantakis, Gianins Promponas, Manthos Dretakis, Panagiotis Papadakos
    Pages 66-71

  9. Data Pipelines for Personalized Exploration of Rated Datasets

    • Sihem Amer-Yahia, Anh Tho Le, Eric Simon
    Pages 72-78

  10. Beyond Accuracy in Link Prediction

    • Javier Sanz-Cruzado, Pablo Castells
    Pages 79-94

  11. A Novel Similarity Measure for Group Recommender Systems with Optimal Time Complexity

    • Guilherme Ramos, Carlos Caleiro
    Pages 95-109

  12. What Kind of Content Are You Prone to Tweet? Multi-topic Preference Model for Tweeters

    • Lorena Recalde, Ricardo Baeza-Yates
    Pages 110-126

  13. Venue Suggestion Using Social-Centric Scores

    • Mohammad Aliannejadi, Fabio Crestani
    Pages 127-142

  14. The Impact of Foursquare Checkins on Users’ Emotions on Twitter

    • Seyed Amin Mirlohi Falavarjani, Hawre Hosseini, Ebrahim Bagheri
    Pages 143-151

  15. Improving News Personalization Through Search Logs

    • Xiao Bai, B. Barla Cambazoglu, Francesco Gullo, Amin Mantrach, Fabrizio Silvestri
    Pages 152-166

  16. Analyzing the Interaction of Users with News Articles to Create Personalization Services

    • Alessandro Celi, Alejandro Piad, Jósval Díaz Blanco, Romina Eramo
    Pages 167-180

  17. Using String-Comparison Measures to Improve and Evaluate Collaborative Filtering Recommender Systems

    • Luiz Mario Lustosa Pascoal, Hugo Alexandre Dantas do Nascimento, Thierson Couto Rosa, Edjalma Queiroz da Silva, Everton Lima Aleixo
    Pages 181-194

  18. Enriching Product Catalogs with User Opinions

    • Tiago de Melo, Altigran S. da Silva, Edleno S. de Moura, Pável Calado
    Pages 195-204

  19. Correction to: bias goggles: Exploring the Bias of Web Domains Through the Eyes of Users

    • Giannis Konstantakis, Gianins Promponas, Manthos Dretakis, Panagiotis Papadakos
    Pages C1-C1

  20. Back Matter

    Pages 205-205
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About this book

This book constitutes refereed proceedings of the First International Workshop on Algorithmic Bias in Search and Recommendation, BIAS 2020, held in April, 2020. Due to the COVID-19 pandemic BIAS 2020 was held virtually. 

The 10 full papers and 7 short papers were carefully reviewed and seleced from 44 submissions. The papers cover topics that go from search and recommendation in online dating, education, and social media, over the impact ofgender bias in word embeddings, to tools that allow to explore bias and fairnesson the Web. 

Editors and Affiliations

  • Eurecat - Centre Tecnològic de Catalunya, Barcelona, Spain

    Ludovico Boratto

  • Unitelma Sapienza University of Rome, Rome, Italy

    Stefano Faralli

  • University of Cagliari, Cagliari, Italy

    Mirko Marras

  • University of L’Aquila, L’Aquila, Italy

    Giovanni Stilo

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