Figure - available from: Scientific Reports
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Dynamics for the 8 most used primary keywords tagging the NYT articles (shortened names used in the labels). The vertical axis shows the number of primary keyword usages on each day, smoothed with a rolling average over 7 days to eliminate structure introduced by weekends (see Supplementary Material).
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We study the dynamics of interactions between a traditional medium, the New York Times journal, and its followers in Twitter, using a massive dataset. It consists of the metadata of the articles published by the journal during the first year of the COVID-19 pandemic, and the posts published in Twitter by a large set of followers of the @nytimes acc...
Citations
... One of the classic research lines in sociophysics is the temporal dynamics of the public agenda, which involves tracking topics across various domains-economics, politics, culture-that emerge from processing large sets of articles published in the media (Pinto et al., 2019;Gozzi et al., 2020;Schawe et al., 2023). At the other end of the scale, the temporal consumption of individual words, such as X (ex Twitter) hashtags, has also been studied (Altmann et al., 2013;Lorenz-Spreen et al., 2019;Lin et al., 2021;Pardo Pintos et al., 2022). ...
The digital revolution has transformed the exchange of information between people, blurring the traditional roles of sources and recipients as active and passive entities. To study this, we build on a publicly available database of quotes, organized as units of information flowing through media and blogs with minimal distortion. Building on this, we offer an innovative interpretation of the observed temporal patterns through a minimal model with two ingredients: a two-way feedback between sources and recipients, and a delay in the media’s response to activity on blogs. Our model successfully fits the variety of observed patterns, revealing different attention decays in media and blogs, with rebounds of information typically occurring between 1 and 4 days after the initial dissemination. More important perhaps, the model uncovers a functional relationship between the rate of information flow from media to blogs and the decay of public attention, suggesting a simplification in the mechanisms of information exchange in digital media. Although further research is required to generalize these findings fully, our results demonstrate that even a bare-bones model can capture essential mechanisms of information dynamics in the digital environment.
