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The current study took a meta-analytical approach to summarize the results from earlier studies that had attempted to answer the question about who is tweeting scientific content. The methodological challenges of our approach stemmed from the earlier studies using different data and somewhat different categorizations. Our results demonstrate the importance of individuals, and in particular individual academics, in the dissemination of scientific articles on Twitter. Our results also highlight the need for a more structured and unified categorization, as a significant proportion of the results in earlier studies have been unclear.
| 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 | 2 | |
| downloads | 3 |

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