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

Date
2017-01-04
Authors
Bechmann, Anja
Journal Title
Journal ISSN
Volume Title
Publisher
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.
Description
Keywords
digital sociology, DNN, picture recognition, social media images, vision algorithms
Citation
Rights
Access Rights
Email libraryada-l@lists.hawaii.edu if you need this content in ADA-compliant format.