El potencial de las redes basadas en la API Google Vision para el estudio de imágenes digitales nativas

Omena, Janna Joceli; Pilipets, Elena; Gobbo, Beatrice; Jason, Chao

doi:10.7764/disena.19.article.1

Cited by 13 publications

(7 citation statements)

References 20 publications

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“…Comparable to a reverse image search, the feature processes the information across images and associated text using metadata embedded in the images' current online locations. By leveraging the capabilities of the Google Knowledge Graph (Burkhardt and Rogers, 2022;Omena et al, 2021), the method provides contextual clues to each of the images in terms of their literal content (e.g. 'forehead', 'clothing', 'muscle'), their associated web locations (e.g.…”

Section: Methods: Online Images Memeification and The Value Of Outliersmentioning

confidence: 99%

Memetic commenting: Armenian curses and the Twitter theatre of Trump's deselection

Pilipets,

Paasonen

2024

International Journal of Cultural Studies

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On 7 November 2020, strange things were happening in the comments to @realDonaldTrump's tweet erroneously arguing that he had won the US presidential election, ‘BY A LOT’. Posting quote tweets and replies in Armenian in tandem with ‘cursed images’, memes, and creepypasta, users engaged in a spam-like trollish intervention, even as Twitter kept removing the said content in real time. Exploring this online incident through various analytical techniques, this article first attends to absurdity and ephemerality within the polarized social media event. Second, it makes an argument for the productivity of digital methods in cultural studies inquiry aiming to understand the temporal, contextual, and infrastructural aspects of memetic commenting. Third, by focusing on the social (media) theatre of Armenian curses, we make a case for the analytical importance of studying materials deemed niche and anomalous in networked exchanges.

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Section: Methods: Online Images Memeification and The Value Of Outliersmentioning

confidence: 99%

Memetic commenting: Armenian curses and the Twitter theatre of Trump's deselection

Pilipets,

Paasonen

2024

International Journal of Cultural Studies

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“…In 2012, the Yale Computer Graphics Group developed a plugin for the then newly born network visualisation and exploration software Gephi (Bastian, Heymann and Jacomy, 2009). This plugin -ImagePreview-has opened up new horizons for visual methods, facilitating, for example, network vision analysis (see Omena et al, 2021) and influencing the development of other research software, like Memespector Graphical User Interface (Chao, 2021).…”

Section: Mapping Visual Methodsmentioning

confidence: 99%

Researching visual protest and politics with “extra-hard” data

Özkula,

Omena,

Gajjala

2024

JDSR

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A range of scholars have criticised scholarly tendencies to focus on “easy” data such as provided by the low-hanging fruit of Twitter hashtag networks (Burgess & Bruns, 2015; Hargittai, 2020; Tromble, 2021). As a result, digital social research has been said to create a glut of studies that favour particular platforms, data forms, and networking dynamics, choices that may create ‘digital bias’ (Marres, 2017). These issues are particularly significant in visual data as the implicit nature of visuality means that platform spaces, text, and networked uses of visuals contribute to how visuals are interpreted in digital environments. In response to this issue, we present and critically reflect on new potentialities in software-based visual research on protest and politics, including: (1) rich cross-project comparisons; (2) complementing platform data with on-the-ground engagement, and (3) quali-quanti visual methods. These allow for rich data journeys through multi-modality, hybridity, comprehensive data curation, reiterative image data collection and interpretation, and the inclusion of contextual reflections in focused visual research, elements that provide meaning, texture, and context (= extra-hard data). We argue that visual digital methods consequently have the potential to provide nuanced, robust, and versatile analysis of visual data, if not necessitate these in a post-API age in which easy data access is no longer a given.

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“…This method was adapted from Omena et al (2020, 2021) which utilizes computer vision algorithm (i.e., Google Vision API) in the classification and organization of large social media image corpora. The goal of this method is to discover visual discourses by identifying repeated use of similar visuals in the corpus, which is indicated by clusters of similar images in an image-label bi-partite network.…”

Section: Methodsmentioning

confidence: 99%

“We are snowflakes”: Minor transnationalism and the cultural resilience of slash fanfiction community in China

Fan

2023

Global Media and China

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This article examines the cultural resilience of the Chinese slash fanfiction subculture. Popular among Chinese youth, the writing and reading of slash are subjected to increasingly stringent regulations due to changes in the political environment. Drawing from the theoretical framework of minor transnationalism, the current study situates the development of the Chinese slash community in the context of post-socialist reform and globalization, arguing that slash fanfiction is a form of non-institutional, border-crossing cultural practice that challenges orthodox heteronormativity in nationalistic discourses. Foregrounding the double-edge-sword role of digital platforms, this article dissects the cultural resilience of the Chinese slash community—manifested as various strategies in keeping the viability of their cultural practices, including cultural enclosure, border-crossing platform-switching, and social media activism. This article contributes to the study of subcultures by bringing a transnational perspective that focuses on continuous, resilient cultural practices in negotiations of alternative cultural and political agendas. Methodologically, it also contributes to social media ethnographic research by testing out a comprehensive toolkit that combines close reading with computational text-mining and visual network analysis in the analysis of multimodal social media discourses.

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El potencial de las redes basadas en la API Google Vision para el estudio de imágenes digitales nativas

Cited by 13 publications

References 20 publications

Memetic commenting: Armenian curses and the Twitter theatre of Trump's deselection

Memetic commenting: Armenian curses and the Twitter theatre of Trump's deselection

Researching visual protest and politics with “extra-hard” data

“We are snowflakes”: Minor transnationalism and the cultural resilience of slash fanfiction community in China

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