A Tale of Two Cultures: Comparing Interpersonal Information Disclosure Norms on Twitter

TL;DR

This study compares online interpersonal disclosure norms on Twitter between the U.S. and India, revealing cultural differences in emotion, topics, and content through a large-scale analysis of tweets and a novel detection method.

Contribution

It introduces a culturally-sensitive taxonomy and a high-accuracy detector for interpersonal disclosures on Twitter, highlighting online cultural differences in self-disclosure.

Findings

Differences in expressed emotion about family between U.S. and India.

Variations in topics and content disclosed across cultures.

Demonstrates the importance of mixed methods for analyzing online cultural norms.

Abstract

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.