Name
Abstract | ||
|---|---|---|
In recent years, there has been an unprecedented growth in content that is shared and presented on social media platforms. Along with this growth, however, there is an increasing concern over the lack of control social media users have on the content they are shown by invisible algorithms. In this paper, we introduce Gobo, an open-source social media browser system that enables users to manage and filter content from multiple platforms on their own. Gobo aims to help users control what's hidden from their feeds, add perspectives from outside their network to help them break filter bubbles, and explore why they see certain content on their feed. Through an iterative design process, we've built and deployed Gobo in the wild and conducted a pilot study in the form of a survey to understand how the users respond to the shift of control from invisible algorithms to themselves. Our initial findings suggest that Gobo has potential to provide an alternate design space to enhance control, transparency, and explainability in social media.
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Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3311957.3359452 | Conference Companion Publication of the 2019 on Computer Supported Cooperative Work and Social Computing |
Keywords | DocType | ISBN |
algorithmic accountability, algorithmic transparency | Conference | 978-1-4503-6692-2 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rahul Bhargava | 1 | 0 | 0.68 |
| Anna Chung | 2 | 0 | 0.34 |
| Snehalkumar (Neil) S. Gaikwad | 3 | 12 | 1.21 |
| Alexis Hope | 4 | 2 | 0.69 |
| Dennis Jen | 5 | 0 | 0.68 |
| Jasmin Rubinovitz | 6 | 0 | 0.34 |
| Belén Saldías-Fuentes | 7 | 0 | 0.34 |
| Ethan Zuckerman | 8 | 47 | 5.54 |