A Method to Analyze Multiple Social Identities in Twitter Bios

TL;DR

This paper introduces a new method for analyzing how Twitter users express multiple social identities in their bios, focusing on identifying personal identifiers to better understand self-presentation online.

Contribution

It defines the concept of personal identifiers, develops a method to extract them from bios, and validates this approach to improve social identity analysis in social media texts.

Findings

Successfully identified and extracted personal identifiers from Twitter bios.

Validated the method's effectiveness and limitations.

Provides new tools for social psychological and social media research.

Abstract

Twitter users signal social identity in their profile descriptions, or bios, in a number of important but complex ways that are not well-captured by existing characterizations of how identity is expressed in language. Better ways of defining and measuring these expressions may therefore be useful both in understanding how social identity is expressed in text, and how the self is presented on Twitter. To this end, the present work makes three contributions. First, using qualitative methods, we identify and define the concept of a personal identifier, which is more representative of the ways in which identity is signaled in Twitter bios. Second, we propose a method to extract all personal identifiers expressed in a given bio. Finally, we present a series of validation analyses that explore the strengths and limitations of our proposed method. Our work opens up exciting new opportunities at the intersection between the social psychological study of social identity and the study of how we compose the self through markers of identity on Twitter and in social media more generally.