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 largescale 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.
An approach for the determination and correlation of diversity and efficiency of software development teams
