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

Simple item page
dc.contributor.authorBechmann, Anja
dc.date.accessioned2016-12-29T00:44:40Z
dc.date.available2016-12-29T00:44:40Z
dc.date.issued2017-01-04
dc.description.abstractThis 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.
dc.format.extent9 pages
dc.identifier.doi10.24251/HICSS.2017.218
dc.identifier.isbn978-0-9981331-0-2
dc.identifier.urihttp://hdl.handle.net/10125/41372
dc.language.isoeng
dc.relation.ispartofProceedings of the 50th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectdigital sociology
dc.subjectDNN
dc.subjectpicture recognition
dc.subjectsocial media images
dc.subjectvision algorithms
dc.titleKeeping it Real: From Faces and Features to Social Values in Deep Learning Algorithms on Social Media Images
dc.typeConference Paper
dc.type.dcmiText

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
paper0223.pdf
Size:
2.63 MB
Format:
Adobe Portable Document Format
Download

Collections

Critical and Ethical Studies of Digital and Social Media Minitrack