A Proposal for Cross-language Analysis: violence against women and the Web.

Aim of the paper is investigating the mood on the Web with respect to one of the most relevant Human Rights violation, without any geographic distinction: the violence against women. While the literature that studies the phenomenon is rapidly growing, the action field is still fragile and the question marks are about the relationship between the public opinion and the contextual factors. In a first look at the phenomenon, we aim at mapping gender violence on the Web, in a Big Data perspective. The peculiar problem we deal with consists in analysing short documents (tweets) written in six European different languages, in the occasion of a common event: the International Day for the Elimination of Violence against Women, 25 November 2017. For our statistical analysis, we choose a multi-linguistic, cross-national perspective. The basic idea is that there are some common structures, language independent ("concepts"), which are declined in the different national natural language expressions ("terms"). Investigating those structure (e.g. factors of lexical correspondence analyses separately performed on the different collections), enables a double level analysis trying to understand and visualise national peculiarities and communalities. The statistical tool is given by Procrustes rotations. Keywords: Big Data, Text Mining, Cross-national study, Procrustes rotations