  In this study, we tested the robustness of three communication networks
extracted from the online forums included in the intranet platforms of three
large companies. For each company we analyzed the communication among employees
both in terms of network structure and content (language used). Over a period
of eight months, we analyzed more than 52,000 messages posted by approximately
12,000 employees. Specifically, we tested the network robustness and the
stability of a set of structural and semantic metrics, while applying several
different node removal strategies. We removed the forum moderators, the
spammers, the overly connected nodes and the nodes lying at the network
periphery, also testing different combinations of these selections. Results
indicate that removing spammers and very peripheral nodes can be a relatively
low impact strategy in this context; accordingly, it could be used to clean the
noise generated by these types of social actor and to reduce the computation
complexity of the analysis. On the other hand, the removal of moderators seems
to have a significant impact on the network connectivity and the shared
content. The most affected variables are closeness centrality and contribution
index. We also found that the removal of overly connected nodes can
significantly change the network structure. Lastly, we compared the behavior of
moderators with the other users, finding distinctive characteristics by which
moderators can be identified when their list is unknown. Our findings can help
online community managers to understand the role of moderators within intranet
forums and can be useful for social network analysts who are interested in
evaluating the effects of graph simplification techniques.
