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The presented data pertains to predictions of Attitudes and CTM, generated through the application of Machine Learning models. These models have been extensively elucidated in the research paper titled "From Tribal Polarization to Socio-Economic Disparities: Exploring the Landscape of Vaccine Hesitancy on Twitter". The aforementioned data is available to the public.
Contextualized topic modeling, Attitude analysis, Twitter, COVID-19, political beliefs, trust in institutions, Vaccine hesitancy, universal moral foundations
Twitter Data
Contextualized topic modeling, Attitude analysis, Twitter, COVID-19, political beliefs, trust in institutions, Vaccine hesitancy, universal moral foundations
Twitter Data
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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| downloads | 1 |

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