## 7 Use-Case Analysis
### Competence Analysis: Are There Detectable Gender Differences?  
Finally, we analyzed gendered network behavior as a function of discussed topics. Our results show that women are active also in networks dealing with very technical topics. For example, the previous Figure 5 shows that the social network of users discussing about _big data_ is led by a woman; furthermore, there are three women among the top five LCR.  
A more systematic analysis of competences as a function of topic and thread categories is summarized in Table 3. Topics and threads have been classified as described in Section 5.4. We remind that we considered only a subset of 393 topics and 4261 threads showing a strong membership to a single category. The first two rows of the table show, as expected, that the ESN is used mainly to discuss about technical and organization/administrative issues, while leisure topics are a minority. The subsequent rows show the percentage of women among the first top leaders and brokers in the two networks originated by the subset of classified topics and threads. The percentage of women participation in these two networks was 20.7% and 20.1%, respectively. These values represent the prior probability against which values in rows 3-6 of Table 3 should be compared.  
When restricting to focused topics, women leadership and intermediary skills are significantly greater than what would be expected given their minority presence in the network. These results are stronger than in Table 2, showing that, as pointed out in several recent articles (e.g., [[http://www.theatlantic.com/magazine/archive/2014/05/the-confidence-gap/359815/](http://www.theatlantic.com/magazine/archive/2014/05/the-confidence-gap/359815/)]([http://www.theatlantic.com/magazine/archive/2014/05/the-confidence-gap/359815/](http://www.theatlantic.com/magazine/archive/2014/05/the-confidence-gap/359815/)), accessed on 1 September 2021), women are more competent than confident. Table 3 also clearly shows that women are equally active in technical and organization topics. This is very interesting since it contradicts the stereotype that women are less competent than men in technical subjects.  
\begin{table}
\begin{tabular}{l l l l} \hline \hline  & **Technical** & **Leisure** & **Organ/Admin** \\ \hline n. of classified threads & 2340 (54.9\%) & 157 (3.7\%) & 1767(41.4\%) \\ n. of classified topics & 218 (55.5\%) & 35 (8.9\%) & 140 (20\%) \\ \% females in top topic LCR & 40.0\% & 40.0\% & 40.0\% \\ \% females in top thread LCR & 20.0\% & 50.0\% & 40.0\% \\ \% females in top topic LBR & 50.0\% & 60.0\% & 50.0\% \\ \% females in top thread LBR & 50.0\% & 50.0\% & 40.0\% \\ \hline \hline \end{tabular}
\end{table}
Table 3: Leadership and brokerage as a function of topics/threads categories.  
In conclusion, our case study, supported by the implemented platform and measures, has led to a number of interesting results concerning the common behaviors of co-workers:  
1. Women are significantly more gender homophilous than males, while males are homophilous by role in the first place, and then by gender.
2. The network leadership analysis has clearly shown that women co-workers are top central leaders proportional to their male colleagues, but they are top brokers significantly more than what would be expected given their presence in the network. We also found that female central leaders are also central brokers more often than males; thus, females embody the notion of network leader better than males. Furthermore, female leaders, contrary to what is observed for the total female population, are gender-neutral, as it should be: a good leader is willing to collaborate and engage their colleagues regardless of gender.
3. Concerning competence, our topic-oriented classification of users' conversations has shown that women are equally competent (and leaders) in technical, administrative, and organizational issues, thus contradicting the stereotype of their lower expertise in technical subjects.