Italian happy parents in Twitter

This article explores opinions and semantic orientation around fertility and parenthood by scrutinizing filtered Italian Twitter data. We propose a novel methodological framework relying on Natural Language Processing techniques for text analysis, which is aimed at extracting sentiments from texts. A manual annotation for exploring sentiment and attitudes to fertility and parenthood was applied to Twitter data. The resulting set of tweets (corpus) was analysed through sentiment and emotion lexicons in order to highlight how affective language is used in this domain. It emerges that parents express a generally positive attitude towards their children and being and become parents, but quite negative sentiments on children’s future, politics and fertility and also parental behaviour. Exploiting geographical information from tweets, we find a significant correlation between the prevalence of positive sentiments about parenthood and macro-regional indicators for both life satisfaction and fertility levels.