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The dataset contains Tweet IDs along with the location and tweet timestamp. The tweets are labeled based on motivating/demotivating status, stance towards the COVID-19 vaccine, and topic in the tweet text. To comply with Twitter guidelines, we removed the tweet texts and author information. You can use Hydrator API to hydrate the tweets. The repository also contains the machine-learning models for topic modeling, de/motivation classifier, and stance detection from the tweets.
topic, covid-19, vaccine, twitter, stance
Twitter Data
topic, covid-19, vaccine, twitter, stance
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 |
| views | 18 | |
| downloads | 25 |

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