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This paper explores how individuals' language use in gender-specific groups ("mothers" and "fathers") compares to their interactions when referred to as "parents." Language adaptation based on the audience is well-documented, yet large-scale studies of naturally-occurring audience effects are rare. To address this, we investigate audience and gender effects in the context of parenting, where gender plays a significant role. We focus on interactions within Reddit, particularly in the parenting Subreddits r/Daddit, r/Mommit, and r/Parenting, which cater to distinct audiences. By analyzing user posts using word embeddings, we measure similarities between user-tokens and word-tokens, also considering differences among high and low self-monitors. Results reveal that in mixed-gender contexts, mothers and fathers exhibit similar behavior in discussing a wide range of topics, while fathers emphasize more on educational and family advice. Single-gender Subreddits see more focused discussions. Mothers in r/Mommit discuss medical care, sleep, potty training, and food, distinguishing themselves. In terms of individual differences, we found that, especially on r/Parenting, high self-monitors tend to conform more to the norms of the Subreddit by discussing more of the topics associated with the Subreddit. [ABSTRACT FROM AUTHOR]

Ordinary computers can perform machine learning by comparing mathematical representations of data. An experiment demonstrates how quantum computing could use quantum-mechanical representations instead. How quantum computers could be used to learn from data. [ABSTRACT FROM AUTHOR]