extended-abstract

Exploring the Community of Model Publishers on TensorFlow Hub

Authors:

Hyunggu JungAuthors Info & Claims

CSCW'22 Companion: Companion Publication of the 2022 Conference on Computer Supported Cooperative Work and Social Computing

Pages 63 - 67

https://doi.org/10.1145/3500868.3559477

Published: 08 November 2022 Publication History

Abstract

We explore the community of AI model publishers on TensorFlow Hub (TF Hub). While researchers identified the challenges AI model publishers and AI model users faced, little is known about how they interact with each other in an online community. The analysis of the metadata recorded on TF Hub revealed the models that the AI model publishers uploaded. Also, we found out how the models published by the AI model publishers were shared with other people on TF Hub. To our knowledge, this is the first attempt to explore the online community of AI model publishers sharing their models with each other.

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Cited By

Yoo TLee HOh SKwon HJung H(2023)Visualizing the Carbon Intensity of Machine Learning Inference for Image Analysis on TensorFlow HubCompanion Publication of the 2023 Conference on Computer Supported Cooperative Work and Social Computing10.1145/3584931.3606959(206-211)Online publication date: 14-Oct-2023
https://dl.acm.org/doi/10.1145/3584931.3606959

Index Terms

Exploring the Community of Model Publishers on TensorFlow Hub
1. Human-centered computing
  1. Collaborative and social computing
    1. Empirical studies in collaborative and social computing

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Information & Contributors

Information

Published In

cover image ACM Conferences

CSCW'22 Companion: Companion Publication of the 2022 Conference on Computer Supported Cooperative Work and Social Computing

November 2022

318 pages

ISBN:9781450391900

DOI:10.1145/3500868

Editors:
Gary Hsieh
University of Washington, Seattle, USA
,
Anthony Tang
University of Toronto, Toronto, Canada
,
Morgan G. Ames
University of California Berkeley, Berkeley, USA
,
Sharon Ding
University of Glasgow, Glasgow, UK
,
Susan Fussell
Cornell University, Ithaca, USA
,
Vera Liao
Microsoft Research, Montreal, Canada
,
Andrés Monroy-Hernández
Princeton University, Princeton, USA
,
Sean Munson
University of Washington, Seattle, USA
,
Irina Shklovski
University of Copenhagen, Copenhagen, Denmark
,
John Tang
Microsoft Research, Sunnyvale, USA

Copyright © 2022 Owner/Author.

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

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Publication History

Published: 08 November 2022

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Extended-abstract
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National Research Foundation of Korea

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CSCW '22

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SIGCHI

CSCW '22: Computer Supported Cooperative Work and Social Computing

November 8 - 22, 2022

Virtual Event, Taiwan

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Overall Acceptance Rate 2,235 of 8,521 submissions, 26%

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October 18 - 22, 2025

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Cited By

Yoo TLee HOh SKwon HJung H(2023)Visualizing the Carbon Intensity of Machine Learning Inference for Image Analysis on TensorFlow HubCompanion Publication of the 2023 Conference on Computer Supported Cooperative Work and Social Computing10.1145/3584931.3606959(206-211)Online publication date: 14-Oct-2023
https://dl.acm.org/doi/10.1145/3584931.3606959

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