Search results

Mapping microplastics

Mapping Microplastics was a first exploratory workshop (part of the Entrepreneurship Program at HvA) with researchers and entrepreneurs to map how the public discourse on microplastics develops on Twitter.The preparation of this workshop followed a hybrid approach in three steps: preliminary mapping, joint interpretation and annotation, map redesign and feedback. The preliminary mapping was performed by designing a query to collect tweets around the topic of Microplastics. To perform the data collection and preliminary analysis we used TCAT (Twitter Capturing and Analysis Toolset), a tool developed by the Digital Methods Initiative at the University of Amsterdam. A set of four maps was designed to address different sub questions through different visual models: networks of hashtags and users, image grids organized by time and frequency, alluvial diagrams and lists of most interacted with tweets. These maps were used in a joint interpretative hybrid session: the visual material was printed and sent to each partner. With the facilitation of designers and researchers, entrepreneurs annotated the printed maps in parallel online sessions.

Live event-spaces

This chapter investigates the deeply mediatized experience of place and space within the lived practice of events by studying two annual Dutch cultural events as cases: Oerol Festival (2017) and 3FM Serious Request (2017). Drawing on substantial datasets containing online and offline participant observations, both short in situ interviews and longer in-depth interviews with a total of 248 interviewees and large datasets from Twitter and Instagram, this chapter demonstrates that media concurrently de-spatialize, in the sense that they diminish spatial borders and overcome distance, and affirm embodied experiences of being-in-place. I argue that it is liveness - the potential connection, through media, to events that matter to us as they unfold - that creates the closeness between the near and the far elements within the “eventsphere” and binds it all together into one event-space.

Being there live

Machine Vision and Social Media Images: Why Hashtags Matter

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.

Visual Affect in Solidarity Hashtags on Twitter: Toward a New Methodology

Studying images in social media poses specific methodological challenges, which in turn have directed scholarly attention towards 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 circulation and contextualization of images within a socio-technical environment. As the meaning of social media images is co-created by networked 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 is limited. However, combining automated analyses of images - broken down by their compositional elements - with repurposing platform data opens up the possibility to study images in the context of their resonance within and across online discursive spaces. This paper explores the capacities of platform data - hashtag modularity 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 by networked publics that co-create meaning.

The Urban Belonging Photo App: A toolkit for studying place attachments with digital and participatory methods

This paper introduces the open-source Urban Belonging (UB) toolkit, designed to study place attachments through a combined digital, visual and participatory methodology that foregrounds lived experience. The core of the toolkit is the photovoice UB App, which prompts participants to document urban experiences as digital data by taking pictures of the city, annotating them, and reacting to others’ photos. The toolkit also includes an API interface and a set of scripts for converting data into visualizations and elicitation devices. The paper first describes how the app’s design specifications were co-created in a process that brought in voices from different research fields, planners from Gehl Architects, six marginalized communities, and citizen engagement professionals. Their inputs shaped decisions about what data collection the app makes possible, and how it mitigates issues of privacy and visual and spatial literacy to make the app as inclusive as possible. We document how design criteria were translated into app features, and we demonstrate how this opens new empirical opportunities for community engagement through examples of its use in the Urban Belonging project in Copenhagen. While the focus on photo capture animates participants to document experiences in a personal and situated way, metadata such as location and sentiment invites for quali-quantitative analysis of both macro trends and local contexts of people’s experiences. Further, the granularity of data makes both a demographic and post-demographic analysis possible, providing empirical ground for exploring what people have in common in what they photograph and where they walk. And, by inviting participants to react to others’ photos, the app offers a heterogeneous empirical ground, showing us how people see the city differently. We end the paper by discussing remaining challenges in the tool and provide a short guide for using it.