  We present an exploration of cultural norms surrounding online disclosure of
information about one's interpersonal relationships (such as information about
family members, colleagues, friends, or lovers) on Twitter. The literature
identifies the cultural dimension of individualism versus collectivism as being
a major determinant of offline communication differences in terms of emotion,
topic, and content disclosed. We decided to study whether such differences also
occur online in context of Twitter when comparing tweets posted in an
individualistic (U.S.) versus a collectivist (India) society. We collected more
than 2 million tweets posted in the U.S. and India over a 3 month period which
contain interpersonal relationship keywords. A card-sort study was used to
develop this culturally-sensitive saturated taxonomy of keywords that represent
interpersonal relationships (e.g., ma, mom, mother). Then we developed a
high-accuracy interpersonal disclosure detector based on dependency-parsing
(F1-score: 86%) to identify when the words refer to a personal relationship of
the poster (e.g., "my mom" as opposed to "a mom"). This allowed us to identify
the 400K+ tweets in our data set which actually disclose information about the
poster's interpersonal relationships. We used a mixed methods approach to
analyze these tweets (e.g., comparing the amount of joy expressed about one's
family) and found differences in emotion, topic, and content disclosed between
tweets from the U.S. versus India. Our analysis also reveals how a combination
of qualitative and quantitative methods are needed to uncover these
differences; Using just one or the other can be misleading. This study extends
the prior literature on Multi-Party Privacy and provides guidance for
researchers and designers of culturally-sensitive systems.
