Quantifying collective identity online from self-defining hashtags

Barron, Alexander T. J.; Bollen, Johan

doi:10.1038/s41598-022-19181-w

Cited by 2 publications

(2 citation statements)

References 28 publications

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“…Collective identity can become visible online when people adopt certain hashtags, such as #metoo or #blacklivesmatter, or use them in their online profiles. Using hashtags as markers of online collective identity, researchers have studied how these identities organize themselves within social hierarchies (Barron and Bollen 2022), who they interact with, and what they talk about (Chang, Richardson, and Ferrara 2022;Khazraee and Novak 2018). However, while individual identity overlaps with collective identity, it is not synonymous with it and requires further study.…”

Section: Introductionmentioning

confidence: 99%

Non-Binary Gender Expression in Online Interactions

Dorn¹,

Jiang²,

Abramson³

et al. 2023

Preprint

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The presence of non-binary gender individuals in social networks is increasing; however, the relationship between gender and activity within online communities is not well understood and limited by the failures of automated gender recognition algorithms to recognize non-binary individuals. We use natural language processing to investigate individual identity on the Twitter platform, focusing on gender expression as represented by users' chosen pronouns from among 14 different pronoun groups. We find that non-binary groups tend to be more active on the platform, preferring to post messages rather than liking others' messages, compared to binary groups. Additionally, non-binary groups receive more replies, but their messages are reshared and liked less. We also find significant variation in the emotional expressions within nonbinary groups. The study highlights the importance of considering gender as a spectrum, rather than a binary, in understanding online interactions and expression.

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Section: Introductionmentioning

confidence: 99%

Non-Binary Gender Expression in Online Interactions

Dorn¹,

Jiang²,

Abramson³

et al. 2023

Preprint

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show abstract

“…This criterion, combined with an untapped source of Twitter profile data, enables us to extract a large collection of exact instances where users both care about curating their identities and specifically take self-labeling actions (see section 5). The resulting co-labeling behavior captures the relatedness of labels used in public, online identity signaling, a relatedness that can go beyond simple semantic similarity [9,10].…”

Section: Introductionmentioning

confidence: 99%

Online identity as a collective labeling process

2023

Self Cite

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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.

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Quantifying collective identity online from self-defining hashtags

Cited by 2 publications

References 28 publications

Non-Binary Gender Expression in Online Interactions

Non-Binary Gender Expression in Online Interactions

Online identity as a collective labeling process

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