This is the first study to examine language use and sexual self-schemas in natural language data extracted from posts to a large online forum. Recently, two studies applied advanced text analysis techniques to examine differences in language use and sexual self-schemas between women with and without a history of childhood sexual abuse. The aim of the current study was to test the ecological validity of the differences in language use and sexual self-schema themes that emerged between these two groups of women in the laboratory. Archival natural language data were extracted from a social media website and analyzed using LIWC2015, a computerized text analysis program, and other word counting approaches. The differences in both language use and sexual self-schema themes that manifested in recent laboratory research were replicated and validated in the large online sample. To our knowledge, these results provide the first empirical examination of sexual cognitions as they occur in the real world. These results also suggest that natural language analysis of text extracted from social media sites may be a potentially viable precursor or alternative to laboratory measurement of sexual trauma phenomena, as well as clinical phenomena, more generally.
Keywords: childhood sexual abuse; language; meaning extraction method; methodology; social media.