Visual-Based Character Embedding via Principal Component Analysis

He, Linchao; Zhang, Dejun; Tian, Long; Han, Fei; Luo, Mengting; Chen, Yilin; Wu, Yonghong

doi:10.1007/978-981-13-2203-7_16

Cited by 1 publication

(1 citation statement)

References 15 publications

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“…The sub-sample was then split into six three-month intervals (Table 1). We then used a machine learning mode of image classification called img2vec (He et al, 2018) to create plots of visually similar images posted during each interval. The exact workflow used to create the plots is detailed in an online open-science repository that accompanies this article.…”

Section: Materials and Method: 'Following' The Manchester Beementioning

confidence: 99%

Memes, brands and the politics of post-terror togetherness: following the Manchester bee after the 2017 Manchester Arena bombing

Merrill

Lindgren

2021

Information, Communication & Society

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The 22 May 2017 bombing of the Manchester Arena, which killed 22 and injured over 800 more, triggered a massive public response leading to, among other things, improvised memorials, spontaneous vigils, dedicated hashtags, and viral videos. Within this response, the memetic reinvigoration and, subsequently, brand adoption of one of Manchester's oldest civic symbolsthe worker beewas clearly discernible. In this article, we explore how the spread of the bee after the bombing contributed to a politics of post-terror togetherness. Conceptualising memes as 'more or less digital', we 'follow' the bee across bodies, streets and social media platforms via the analysis of approximately 53,000 Instagram images. We show how the initial memeification of the bee carried with it grassroots expressions of togetherness while the subsequent use of the bee in official city branding strategies created and obfuscated various political tensions.

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Section: Materials and Method: 'Following' The Manchester Beementioning

confidence: 99%