Mapping the Positive Self-Bias Embedded in Human Languages

Whether humans inherently view themselves more positively than others underpins a fundamental question in psychology that has eluded scientific consensus for decades. Leveraging advancements in natural language processing to overcome limitations of behavioral research, this study employed word embeddings to investigate more nuanced societal-level positive self-bias in human languages and its universality across cultures and historical periods using multilingual corpora totaling approximately two trillion words. We first validated the presence of positive self-bias in English. Cross-cultural comparisons then revealed self-deprecation tendencies in trait-based self-evaluation in specific Eastern languages, contrasting with Western patterns. However, affective self-positivity—the tendency to associate the self with generally positive rather than negative words—was universally observed across 11 languages. Analysis of 200 years of English texts further substantiated this dichotomy: while trait self-positivity fluctuated historically, affective self-positivity remained stable. These findings support a dual-dimensional model of positive self-bias that reconciles longstanding debates.