Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/41372

Keeping it Real: From Faces and Features to Social Values in Deep Learning Algorithms on Social Media Images

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Item Summary

Title: Keeping it Real: From Faces and Features to Social Values in Deep Learning Algorithms on Social Media Images
Authors: Bechmann, Anja
Keywords: digital sociology
DNN
picture recognition
social media images
vision algorithms
Issue Date: 04 Jan 2017
Abstract: This paper wants to supplement computational tests of deep learning vision algorithms with a sociologically grounded performance test of three widely used vision algorithms on Facebook images (Clarifai, Google Vision and Inception-v3). \ \ The test shows poor results and the paper suggests the use of a two-level labeling model that combines features with theoretically inspired accounts of the social value of pictures for uploaders. The paper contributes a suggestion for labeling categories that connects the two levels, and in conclusion discusses both advantages and disadvantages in accelerating user profiling through a better understanding of the incentives to upload images in the data-driven algorithmic society.
Pages/Duration: 9 pages
URI/DOI: http://hdl.handle.net/10125/41372
ISBN: 978-0-9981331-0-2
DOI: 10.24251/HICSS.2017.218
Rights: Attribution-NonCommercial-NoDerivatives 4.0 International
Appears in Collections:Critical and Ethical Studies of Digital and Social Media Minitrack



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