Die Generalpause: Journalistische Berichterstattung über Musik und Zeitwahrnehmung während des ersten Covid-19-bedingten Lockdowns in Deutschland
General Pause: Journalistic Coverage of Music and Time Perception During the First Covid-19-Related Lockdown in Germany
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Abstract
The lockdown caused by the Covid-19 pandemic during the Spring of 2020 led to extensive changes regarding the daily life of the population, cultural and leisure activities, and mobility. The changes in individual daily routines were not without consequences for the subjective perception of time. The present study examined the newspaper reporting on musical activities and time perception during the lockdown. The data was based on a corpus of 185 newspaper articles from five nationwide German newspapers during the first lockdown (03/16/2020–06/15/2020). Thematic categories were established, categorical connections examined by association rule mining, and the articles’ emotional contents were estimated using sentiment analysis. The content analysis of 185 newspaper articles resulted in a system of 21 thematic categories, and the subsequent association rule mining detected strong connections between the categories “music perception” and “digitization”, as well as “music business”, “live events”, and “economy and finances”. The category “time perception” was connected with “silence and reflection” as well as “public life”, whereas no connection was found between „time perception“ and music related categories. The sentiment analysis revealed a more positive language in articles referring to music, especially for articles in the subcategory “active music making”, while the category “law and politics” had a more negative tone. These results allow insights into public reactions regarding the lockdown and its repercussions. They also suggest a change in individual musical activities in the wake of cancelled live events, balcony concerts, and increased digitization.
Covid-19 pandemic; corona virus; time perception; deceleration; music; news coverage; content analysis; association rule mining; sentiment analysis
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