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Diseña 19 | Visual Methods for Online Images: Collection, Circulation, and Machine Co-Creation

  • September 2021
Authors:
Gabriele Colombo at King's College London
Gabriele Colombo
S. Niederer at Amsterdam University of Applied Sciences
S. Niederer
  • Amsterdam University of Applied Sciences
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Abstract

In an image-saturated society, methods for visual analysis gain urgency. This special issue explores visual ways to study online images, focusing on their collection and circulation. The proposition we make is to stay as close to the material as possible. How to approach the visual with the visual? What type of images may one design to make sense of, reshape, and reanimate online image collections? How may arrangements of online images promote various analytical procedures, participatory actions, and design interventions? Furthermore, we focus on the role that algorithmic tools, including machine vision, can play in such research efforts while being sensitive to their flaws and shortcomings. Which kinds of collaborations between humans and machines can we envision to better grasp and critically interrogate the dynamics of today’s digital visual culture? The different practices and formats discussed in this special issue (including data feminism, visual scores, machine vision, image networks, field guides) offer a range of approaches that seek to understand, reanimate, and change perspectives on our digital visual culture.
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Gabriele Colombo
Sabine niederer
Visual Methods for online iMages: ColleCtion, CirCulation,
and MaChine Co-Creation
19
2021

i
Diseña 19 | Visual Methods for Online Images:
,,
Gabriele Colombo

Sabine Niederer





-













 



Diseña is to

with


-



Gabriele Colombo
Sabine niederer
Visual Methods for online iMages: ColleCtion, CirCulation,
and MaChine Co-Creation
19
2021





tableaux







-
-
en groupe
 














-
-

 




-

Gabriele Colombo
Sabine niederer
Visual Methods for online iMages: ColleCtion, CirCulation,
and MaChine Co-Creation
19
2021



-








Using machine vision to study online natively digital images

-
-

-
audiencing


-

natively
thick


-



Google Images, climate change, and the disappearance of humans

-


-


Gabriele Colombo
Sabine niederer
Visual Methods for online iMages: ColleCtion, CirCulation,
and MaChine Co-Creation
19
2021

-



-



Data-driven curated video catalogs: republishing video footage






-

-

Creating AI art responsibly: a field guide for artists and designers

-

-








Developing online images. From visual traces to public voices

developing-


Gabriele Colombo
Sabine niederer
Visual Methods for online iMages: ColleCtion, CirCulation,
and MaChine Co-Creation
19
2021



-
-



sayingwith
 doingthrough
-


-
expandingcatalogs
revealingtableauxperforming person-
scores 




Conversations about feminist data practices with Catherine D’Ignazio,
Lauren Klein, and Maya Livio

-


-

Data Feminism 
-

-

-





Gabriele Colombo
Sabine niederer
Visual Methods for online iMages: ColleCtion, CirCulation,
and MaChine Co-Creation
19
2021

REFERENCES
Visual Communication: Understanding Images in Media
Culture
 
The  Handbook of Social Media


Proceedings of Machine Learning
Research, 81

First Monday, 24
i
 

Design as We Do in Polimi  
Excavating : The Politics of Images in Machine
Learning Training Sets
Data Feminism


International Journal of Communication, 1 4
 
Social Media + Society, 6

 
Communication
Research and Practice, 2

The Photographic Image in Digital Culture
Networked Images: Visual Methodologies for the Digital Age



 
Mainstreaming the Fringe: How Misinformation Propagates on Social Media

 The
New Inquiry
at-you


Information, CommunicationSociety, 23 

 
The Sociological Review, 62 -

Feminist Data Set
-
Gabriele Colombo
Sabine niederer
Visual Methods for online iMages: ColleCtion, CirCulation,
and MaChine Co-Creation
19
2021

E-Flux Journal,
49
dead
  Gagosian
Quarterly, 



Journal of Medical Internet
Research, 23

The Politics of Social Media Manipulation

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Excavating AI: the politics of images in machine learning training sets
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Full-text available
By looking at the politics of classification within machine learning systems, this article demonstrates why the automated interpretation of images is an inherently social and political project. We begin by asking what work images do in computer vision systems, and what is meant by the claim that computers can “recognize” an image? Next, we look at the method for introducing images into computer systems and look at how taxonomies order the foundational concepts that will determine how a system interprets the world. Then we turn to the question of labeling: how humans tell computers which words will relate to a given image. What is at stake in the way AI systems use these labels to classify humans, including by race, gender, emotions, ability, sexuality, and personality? Finally, we turn to the purposes that computer vision is meant to serve in our society—the judgments, choices, and consequences of providing computers with these capacities. Methodologically, we call this an archeology of datasets: studying the material layers of training images and labels, cataloguing the principles and values by which taxonomies are constructed, and analyzing how these taxonomies create the parameters of intelligibility for an AI system. By doing this, we can critically engage with the underlying politics and values of a system, and analyze which normative patterns of life are assumed, supported, and reproduced.
Going Down the Rabbit Hole?: An Exploration of Network Exposure to Vaccine Misinformation on YouTube
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Full-text available
Background: Social media platforms such as YouTube are hotbeds for the spread of misinformation about vaccines. Objective: To explore how individuals are exposed to anti-vaccine misinformation on YouTube. Methods: Four networks of videos based on YouTube recommendations were collected in November 2019. Two search networks were created from pro- and anti-vaccine keywords to resemble goal-oriented browsing. Two seed networks were constructed from conspiracy and anti-vaccine expert seed videos to resemble direct navigation. Video contents and network structures were analyzed using the Network Exposure Model. Results: Viewers are more likely to encounter anti-vaccine videos through direct navigation starting from an anti-vaccine video than through goal-oriented browsing. In the two seed networks, pro-vaccine videos, anti-vaccine videos, and videos containing health misinformation are all likely to lead to more anti-vaccine videos. Conclusions: YouTube has boosted the search rankings of pro-vaccine videos to diminish the influence of anti-vaccine information. However, when viewers are directed to anti-vaccine videos on YouTube from another site, the recommendation algorithm is still likely to expose them to additional anti-vaccine information.
Machine Vision and Social Media Images: Why Hashtags Matter
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Full-text available
  • Apr 2020
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.
Studying digital images in groups: the folder of images
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  • Jan 2019
Digital images, available online at an unprecedented scale, represent a valuable data source for the study of cultural phenomena. The digital nature of web images requires us to reconsider the approach to their study. I discuss four features of digital images, to make the case for the shift from the individual image to a group of images (i.e. the folder of images) as a main unit of analysis. The four features are: volume, images as data, networked nature, blurriness. As a proposal for an updated approach to visual research, I put forward the design of tailored interfaces for the study of images in groups.
Visual cross-platform analysis: digital methods to research social media images
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  • Jun 2018
Analysis of social media using digital methods is a flourishing approach. However, the relatively easy availability of data collected via platform application programming interfaces has arguably led to the predominance of single-platform research of social media. Such research has also privileged the role of text in social media analysis, as a form of data that is more readily gathered and searchable than images. In this paper, we challenge both of these prevailing forms of social media research by outlining a methodology for visual cross-platform analysis (VCPA), defined as the study of still and moving images across two or more social media platforms. Our argument contains three steps. First, we argue that cross-platform analysis addresses a gap in research methods in that it acknowledges the interplay between a social phenomenon under investigation and the medium within which it is being researched, thus illuminating the different affordances and cultures of web platforms. Second, we build on the literature on multimodal communication and platform vernacular to provide a rationale for incorporating the visual into cross-platform analysis. Third, we reflect on an experimental cross-platform analysis of images within social media posts (n = 471,033) used to communicate climate change to advance different modes of macro- and meso-levels of analysis that are natively visual: image-text networks, image plots and composite images. We conclude by assessing the research pathways opened up by VCPA, delineating potential contributions to empirical research and theory and the potential impact on practitioners of social media communication.
Instagrammatics and digital methods: Studying visual social media, from selfies and GIFs to memes and emoji
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  • Jan 2016
Visual content is a critical component of everyday social media, on platforms explicitly framed around the visual (Instagram and Vine), on those offering a mix of text and images in myriad forms (Facebook, Twitter, and Tumblr), and in apps and profiles where visual presentation and provision of information are important considerations. However, despite being so prominent in forms such as selfies, looping media, infographics, memes, online videos, and more, sociocultural research into the visual as a central component of online communication has lagged behind the analysis of popular, predominantly text-driven social media. This paper underlines the increasing importance of visual elements to digital, social, and mobile media within everyday life, addressing the significant research gap in methods for tracking, analysing, and understanding visual social media as both image-based and intertextual content. In this paper, we build on our previous methodological considerations of Instagram in isolation to examine further questions, challenges, and benefits of studying visual social media more broadly, including methodological and ethical considerations. Our discussion is intended as a rallying cry and provocation for further research into visual (and textual and mixed) social media content, practices, and cultures, mindful of both the specificities of each form, but also, and importantly, the ongoing dialogues and interrelations between them as communication forms.
Fake news and the Dutch YouTube political debate space
Chapter
  • Oct 2020
Disinformation and so-called fake news are contemporary phenomena with rich histories. Disinformation, or the willful introduction of false information for the purposes of causing harm, recalls infamous foreign interference operations in national media systems. Outcries over fake news, or dubious stories with the trappings of news, have coincided with the introduction of new media technologies that disrupt the publication, distribution and consumption of news -- from the so-called rumour-mongering broadsheets centuries ago to the blogosphere recently. Designating a news organization as fake, or der Lügenpresse, has a darker history, associated with authoritarian regimes or populist bombast diminishing the reputation of 'elite media' and the value of inconvenient truths. In a series of empirical studies, using digital methods and data journalism, the authors inquire into the extent to which social media have enabled the penetration of foreign disinformation operations, the widespread publication and spread of dubious content as well as extreme commentators with considerable followings attacking mainstream media as fake.
Nothing new here: Emphasizing the social and cultural context of deepfakes
Article
  • Dec 2019
In the last year and a half, deepfakes have garnered a lot of attention as the newest form of digital manipulation. While not problematic in and of itself, deepfake technology exists in a social environment rife with cybermisogyny, toxic-technocultures, and attitudes that devalue, objectify, and use women’s bodies against them. The basic technology, which in fact embodies none of these characteristics, is deployed within this harmful environment to produce problematic outcomes, such as the creation of fake and non-consensual pornography. The sophisticated technology and metaphysical nature of deepfakes as both real and not real (the body of one person, the face of another) makes them impervious to many technical, legal, and regulatory solutions. For these same reasons, defining the harm deepfakes causes to those targeted is similarly difficult and very often targets of deepfakes are not afforded the protection they require. We argue that it is important to put an emphasis on the social and cultural attitudes that underscore the nefarious use of deepfakes and thus to adopt a more material-based approach, opposed to technological, to understanding the harm presented by deepfakes.
Invisible Images: Your Pictures Are Looking at You
Article
  • Jan 2019
What are the implications of computer vision in relation to machine learning and ‘artificial intelligence’? New York‐based artist and writer Trevor Paglen argues that autonomous image‐interpretation systems, from algorithms that analyse photos on Facebook to licence‐plate readers used by police, constitute a new kind of visuality which is paradoxically largely invisible to human eyes. What is more, this new ‘invisible visuality’ should be understood as a means of centralising power in the hands of the state and corporate actors who are able to deploy machine‐vision systems at scale.