| Summary: | Historians, mostly engaging with written evidence, have argued that the Christianisation of the Roman Empire resulted in changes in both attitudes and behaviour towards children, resulting in a decrease in their maltreatment by society. I begin with a working hypothesis that this attitude-change was real and resulted in a reduction in the maltreatment of children; and that this reduction in maltreatment is evident in the literature. The approach to investigating this hypothesis belongs to the emerging field of digital humanities: by using programming techniques developed in the field of sentiment analysis, I create two sentiment-analysis like tools, one a lexicon-based approach, the other an application of a naive bayes machine learning approach. The latter is favoured as more accurate. The tool is used to automatically tag sentences, extracted from a corpus of texts written between 100 B.C and 600 A.D, that mention children, as to whether the sentences feature the maltreatment of children or not. The results are then quantitively analysed with reference to the year in which the text was written, with no statistically significant result found. However, the high accuracy of the tool in tagging sentences, at above 88%, suggests that similar tools may be able to play an important role, alongside traditional research techniques, in historical and social-science research in the future.
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