Machine Vision and Social Media Images

Why Hashtags Matter

Bibliographic Data

ID2414154
AuthorsMarloes Annette Geboers (0000-0002-3205-7437, Amsterdam University of Applied Sciences, corresponding author), Chad Thomas Van De Wiele (University of Illinois Chicago)
Year2020
Volume6
Issue2
Publication date2020-04-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueSocial Media + Society (JOURNAL)
Journal identifiersISSN: 2056-3051 • E-ISSN: 2056-3051
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1177/2056305120928485
OpenAlexW3034942044
LanguageEN
Citations received26
References cited49

Studying images in social media poses specific methodological challenges, which in turn have directed scholarly attention toward the computational interpretation of visual data. When analyzing large numbers of images, both traditional content analysis as well as cultural analytics have proven valuable. However, these techniques do not take into account the contextualization of images within a socio-technical environment. As the meaning of social media images is co-created by online publics, bound through networked practices, these visuals should be analyzed on the level of their networked contextualization. Although machine vision is increasingly adept at recognizing faces and features, its performance in grasping the meaning of social media images remains limited. Combining automated analyses of images with platform data opens up the possibility to study images in the context of their resonance within and across online discursive spaces. This article explores the capacities of hashtags and retweet counts to complement the automated assessment of social media images, doing justice to both the visual elements of an image and the contextual elements encoded through the hashtag practices of networked publics

Analytics · Contextualization · Data science · Political science · Politics · Publics · Social media · Social media analytics · World Wide Web · Aesthetic Perception and Analysis · Computer Science · Law in Society and Culture · Psychology · Public Spaces through Art · Artificial Intelligence