Overcoming the Pandemic through Viral Poetry Games: The Phenomenon of Coronavirus-Inspired Digital Acrostic Poetry in South Korea
Bibliographic record
Abstract
Following the outbreak of COVID-19 in South Korea in winter 2019, acrostic poems on the three-syllable word “Corona” became viral on major search engines and social media platforms across the country. The composition of acrostic poems, particularly in three lines, has been a popular cultural phenomenon in Korea since the 1980s when it became a participatory literary exercise and game featured on television entertainment shows. The digital revolution in the 2000s allowed the writing and sharing of these short and whimsical poems to expand into various digital platforms. Since 2010, PC and mobile games have been developed to further enhance the ludic approach to acrostic poetry composition and contests. While facilitating individual creativity, and as an interactive and ludic way of community building and branding, acrostic poetry contests have also been used to promote social and political campaigns and consumer products. This paper will investigate poetry games and contests of acrostic poems on the Coronavirus featured on South Korean digital platforms. It will analyze the various games and contests organized by schools, communities, consumer product brands, and social media circles. The poems, composed by children and adults, display a wide range of messages involving self-reflection, social campaign, political criticism, and subversive wordplay. Together, these viral poems and contests promoted values of collaboration, competition, and social exchange during the pandemic. All in all, the paper explores the viral powers of language and language art in the digital world, as well as digital poetry’s connections to networked self, social mobilization, and online activism.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".