@article{8e7f5ebf6fee4bd8a964aea4c2b742a0,
title = "Online identity as a collective labeling process",
abstract = "Expressing identity socially involves a balance between conformity and innovation. One can adopt existing labels to express belonging to a certain community or introduce new labels to express an individual sense of identity. In such a process of co-creation, the existing identity labels of a community shape one's sense of identity, while individual expression changes that of a community. Social media has introduced new opportunities to study the expression of collective identity. Here we study the group behavior of individuals defining their identities with hashtag self-labels in their Twitter profiles from mid-2017 through 2019. These timelines of personal self-labeling show behavior incorporating innovation, conservation, and social conformity when defining self. We show that the collective co-labeling of popular concepts in the context of identity, such as \#resist and \#maga, follow the dynamics of a modified Yule-Simon model balancing novelty and conformity. The dynamics of identity expression resemble the collective tagging processes of folksonomies, indicating a similarity between the collective tagging of external objects and the collective labeling of ourselves. Our work underpins a better understanding of how online environments mediate the evolution of collective identity which plays an increasingly important role in the establishment of community values and identity politics.",
keywords = "identity, self-labeling, Yule-Simon process, sociophysics, SEMIOTIC DYNAMICS",
author = "A.T.J. Barron and \{ten Thij\}, M. and J. Bollen",
note = "Funding Information: A T J B and J B are grateful for support from the NSF Social, Behavioral and Economic Sciences [SBE] Grant 1636636. A T J B was partially funded by the National Science Foundation NRT Grant 1735095, {\textquoteleft}Interdisciplinary Training in Complex Networks and Systems.{\textquoteright} Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. We thank the Observatory on Social Media and the Network Science Institute at Indiana University, with support from the Knight Foundation and Craig Newman Philanthropies, for making the Twitter profile data available to our analysis. Funding Information: A T J B and J B are grateful for support from the NSF Social, Behavioral and Economic Sciences [SBE] Grant 1636636. A T J B was partially funded by the National Science Foundation NRT Grant 1735095, {\textquoteleft}Interdisciplinary Training in Complex Networks and Systems.{\textquoteright} Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. We thank the Observatory on Social Media and the Network Science Institute at Indiana University, with support from the Knight Foundation and Craig Newman Philanthropies, for making the Twitter profile data available to our analysis. Publisher Copyright: {\textcopyright} 2023 The Author(s). Published by IOP Publishing Ltd.",
year = "2023",
month = apr,
day = "3",
doi = "10.1088/2632-072X/acc62c",
language = "English",
volume = "4",
journal = "Journal of Physics: Complexity",
publisher = "IOP Publishing Ltd.",
number = "2",
}