Table 4 Coefficients of a negative binomial regression model that predicts a paper’s total number of tweet mentions

From: The gender gap in scholarly self-promotion on social media

 

Dependent variable:

 

The total number of tweets

Woman x (Self-promotion = True)

−0.127 (p < 0.001)

Woman

0.148 (p < 0.001)

Self-promotion = True

1.235 (p < 0.001)

Authorship first position

0.110 (p < 0.001)

Authorship middle position

0.290 (p < 0.001)

Authorship solo author

−0.206 (p < 0.001)

Affiliation rank

−0.008 (p < 0.001)

Affiliation ___location international

0.069 (p < 0.001)

Author previous num. of publications

−0.102 (p < 0.001)

Author log citations

0.050 (p < 0.001)

Author log follower count

0.095 (p < 0.001)

Publication year 2014

0.239 (p < 0.001)

Publication year 2015

0.399 (p < 0.001)

Publication year 2016

0.531 (p < 0.001)

Publication year 2017

0.797 (p < 0.001)

Publication year 2018

0.924 (p < 0.001)

Number of authors

0.001 (p < 0.001)

Journal impact factor

0.065 (p < 0.001)

Intercept

0.364 (p < 0.001)

Fixed effects for research fields

Yes

Observations

618,742

  1. The model additionally controls for the author’s follower count and includes an interaction term between gender and self-promotion. The model is fitted to 618,742 (paper, author) observations where the author is active on Twitter at the paper’s publication date. The significance test is based on the two-sided Wald test. P values are shown in parentheses. Full regression detail is shown in Supplementary Table S15.