Bias and Transparency Seminar

Online, 25th November 2020 at 11.00-12.15 CET

Would you like to take part in a research study to investigate biases in search engine results?

Information bias in search engine results has major impact on users, e.g., from manipulating their knowledge on a topic [1], to influencing voting decision [2]. We are carrying out a research study to investigate information bias, specifically how to increase user awareness of the biases they might find in their search results. As a part of this study, we are inviting students to contribute into our research by participating in a bias and transparency seminar.

Methodology

We will deliver a short lecture to discuss some background about biases in search engines and their impacts on users. You will then be asked to work in a small group to discuss the types of biases that may affect users when they use a news search engine. Afterwards, you will then be invited to create a mock-up design on how a search engine can (and should) inform users of these biases. A short discussion will follow to allow you to discuss your findings with your peers after the activities. The data you provide will be used in our research to inform how bias intervention tools should be developed to assist users when accessing search engines.

More information

This study is funded via the H2020 project CyCAT, whose aim is to raise awareness of algorithmic bias and transparency in social and cultural setting. For more information about the study, please read the participant information sheet or contact Monica Paramita (m.paramita@sheffield.ac.uk) or Frank Hopfgartner (f.hopfgartner@sheffield.ac.uk).

How do you take part?

Please register your email below and we will send you an invitation to the online seminar. We will not use your email address for any other purposes and they will not be affiliated with your data collected in the study.

References
[1] Novin, A., & Meyers, E. (2017). Making Sense of Conflicting Science Information: Exploring Bias in the Search Engine Result Page. In Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval (CHIIR '17). Association for Computing Machinery, New York, NY, USA, 175–184. DOI:https://doi.org/10.1145/3020165.3020185
[2] Epstein, R., & Robertson, R. E. (2015). The search engine manipulation effect (SEME) and its possible impact on the outcomes of elections. Proceedings of the National Academy of Sciences, 112(33), E4512-E4521.