  Understanding how the social context of an interaction affects our dialog
behavior is of great interest to social scientists who study human behavior, as
well as to computer scientists who build automatic methods to infer those
social contexts. In this paper, we study the interaction of power, gender, and
dialog behavior in organizational interactions. In order to perform this study,
we first construct the Gender Identified Enron Corpus of emails, in which we
semi-automatically assign the gender of around 23,000 individuals who authored
around 97,000 email messages in the Enron corpus. This corpus, which is made
freely available, is orders of magnitude larger than previously existing gender
identified corpora in the email domain. Next, we use this corpus to perform a
large-scale data-oriented study of the interplay of gender and manifestations
of power. We argue that, in addition to one's own gender, the "gender
environment" of an interaction, i.e., the gender makeup of one's interlocutors,
also affects the way power is manifested in dialog. We focus especially on
manifestations of power in the dialog structure --- both, in a shallow sense
that disregards the textual content of messages (e.g., how often do the
participants contribute, how often do they get replies etc.), as well as the
structure that is expressed within the textual content (e.g., who issues
requests and how are they made, whose requests get responses etc.). We find
that both gender and gender environment affect the ways power is manifested in
dialog, resulting in patterns that reveal the underlying factors. Finally, we
show the utility of gender information in the problem of automatically
predicting the direction of power between pairs of participants in email
interactions.
