Abstract Purpose Although gender identities influence how people present themselves on social media, previous studies have tested pre-specified dimensions of difference, potentially overlooking other differences and ignoring nonbinary users. Design/methodology/approach Word association thematic analysis was used to systematically check for fine-grained statistically significant gender differences in Twitter profile descriptions between 409,487 UK-based female, male, and nonbinary users in 2020. A series of statistical tests systematically identified 1,474 differences at the individual word level, and a follow up thematic analysis grouped these words into themes. Findings The results reflect offline variations in interests and in jobs. They also show differences in personal disclosures, as reflected by words, with females mentioning qualifications, relationships, pets, and illnesses much more, nonbinaries discussing sexuality more, and males declaring political and sports affiliations more. Other themes were internally imbalanced, including personal appearance (e.g. male: beardy; female: redhead), self-evaluations (e.g. male: legend; nonbinary: witch; female: feisty), and gender identity (e.g. male: dude; nonbinary: enby; female: queen). Research limitations The methods are affected by linguistic styles and probably under-report nonbinary differences. Practical implications The gender differences found may inform gender theory, and aid social web communicators and marketers. Originality/value The results show a much wider range of gender expression differences than previously acknowledged for any social media site.

中文翻译：

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英国推特自我描述中的男性、女性和非二元差异：细粒度的系统探索

摘要目的 尽管性别认同会影响人们在社交媒体上的展示方式，但之前的研究已经测试了预先指定的差异维度，可能会忽略其他差异并忽略非二元用户。设计/方法/方法 词关联主题分析用于系统检查 2020 年 409,487 名英国女性、男性和非二元用户之间 Twitter 个人资料描述中的细粒度统计显着性性别差异。一系列统计测试系统地确定了 1,474 个差异在单个单词级别，后续主题分析将这些单词分组为主题。结果 结果反映了兴趣和工作的离线变化。他们还表现出个人披露方面的差异，如语言所反映的那样，女性更多地提到资格、人际关系、宠物和疾病，非二元性更多地讨论性行为，而男性则更多地宣布政治和体育从属关系。其他主题在内部是不平衡的，包括个人外表（例如男性：大胡子；女性：红头发）、自我评价（例如男性：传奇；非二元：女巫；女性：好斗）和性别认同（例如，男性：花花公子；非二元：恩比） ; 女性：女王）。研究局限 这些方法受语言风格的影响，可能低估了非二元差异。实际意义 所发现的性别差异可能会为性别理论提供信息，并有助于社交网络传播者和营销人员。原创性/价值 结果显示，性别表达差异的范围比之前任何社交媒体网站所承认的要广泛得多。