Name
Abstract | ||
|---|---|---|
Twitter users signal social identity in their profile descriptions, or bios, in a number of important but complex ways that \hl{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 \hl{identify and} define the concept of a personal identifier, which is more \hl{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. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1145/3479502 | Proc. ACM Hum. Comput. Interact. |
DocType | Volume | Issue |
Conference | 5 | CSCW2 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Arjunil Pathak | 1 | 0 | 0.34 |
| Navid Madani | 2 | 0 | 0.34 |
| Kenneth Joseph | 3 | 9 | 5.91 |