deletions | additions       diff --git a/In_Figurereffigscatterplots_we_show.tex b/In_Figurereffigscatterplots_we_show.tex  index d28bb27..951eb96 100644  --- a/In_Figurereffigscatterplots_we_show.tex  +++ b/In_Figurereffigscatterplots_we_show.tex 
...
In Figure~\ref{fig:scatterplots} Figure 7  we show the bivariate scatterplots between Twitter mentions, arXiv downloads and citations. The corresponding Pearson's correlation coefficients are shown as well. Figure~\ref{fig:tvsc} Figure 7(b)  and \ref{fig:avsc} 7(c)  again show that Twitter mentions are correlated with citations better than arXiv downloads, which matches our results obtained from multivariate linear regression analysis. In addition, Twitter mentions are also positively correlated with arXiv downloads as is shown in Figure~\ref{fig:tvsa}, Figure 7(a),  suggesting that the Twitter attention received by an article can be used to estimate its usage data, but usage, in turn, does not seem to correlated to early citations. Given the rather small sample size and the unequally distributed scatter, we performed a delete-1 observation jackknife on the Pearson's correlation coefficient between Twitter mentions and early citations (N=70). This yields a modified correlation value of 0.430 vs. the original value of 0.4516 indicating that the observed correlation is rather robust. However, dropping the top two frequently tweeted articles does reduce the correlation to 0.258 (p=0.016) implying that the observed correlation is strongest when frequently mentioned articles on Twitter are included, matching the results reported by \cite{Eysenbach_2011}.