Gender-based violence (GBV) is an important and persistent problem that affects our society. There is an urgent demand for measuring and monitoring the phenomenon from different perspectives to prevent, protect the victims and prosecute perpetrators of violence. Since GBV and Violence against women (VAW) are complex phenomena, it is preferable to address them using different sources and techniques. Some of them are more useful to estimate prevalence and incidence indicators, to give light to the hidden and unreported part of the phenomenon, to study the risks’ factors and causes and consequences of violence, like the survey on populations; while others sources as the census on shelters or the administrative data collections are more suitable to provide information on the protection and the response of the State. Recent works by Tur-Prats (2019), Gonzalez & Rodrıguez-Planas (2020) and Alesina et al. (2020), document the prominent role of cultural and social norms, which mainly refer to sexual stereotypes and the role of women in society. The strong lengths between gender stereotypes and the level of acceptance of GBV in Italy were also studied during the lockdown period. This study suggests that the media campaign's success (aimed at raising awareness to use the National Helpline against GBV and stalking) is, to some extent, responsive to women’s stereotypes rather than female economic status. So these studies raise questions on how to design appropriate interventions to encourage reporting of abuse and ultimately taper domestic violence. If only income matters, policymakers should invest in programs to reinforce women’s autonomy via improvements in labour market opportunities and the expansion of shelter availability. However, it is crucial to provide data related to the presence of Gender Stereotypes because they play a substantial role in combating the GBV. Neglecting the relevance of social norms might lead to an imperfect understanding of GBV and domestic violence and the mechanisms that incentivise reporting abuse and, in turn, loosely designed policies. This implies putting more effort into exploring the Gender Stereotype and the social image of violence, trying to connect periodically with new data sources. The new framework of big data can be considered a new frontier of statistical knowledge of social phenomena. Among the various available sources of Big Data, social media constitute a particularly useful resource of information for analysing the phenomenon of gender-based violence, cyber-violence and gender stereotypes. A challenging problem in this context is using this data to produce official statistics representative of the target population. No randomised sampling design facilitates the generalization of conclusions and results obtained with the available data to an intended larger target population. Hence, extracting statistically relevant information from these sources is challenging (Daas and Puts, 2014). It is important to underline that this paper is focused on describing the method adopted by enhancing the contents of the social media but doesn’t affect the crucial question related to the representative statistical sample of this content. It will be the second stage of this project. There is a growing concern about various issues associated with social media data. Boyd and Crawford (2012) ask whether such data may alter what “research” means and call for the need to question relevant assumptions and biases. Bright and al. (2014) argue that caution is needed when interpreting social media data, and major questions remain on how to employ such data properly. Hsieh and Murphy (2017) highlight what they call coverage error, query error and interpretation error in relation to Twitter data. Halford and al. (2017) underline the urgency to develop a better understanding of the construction and circulation of social media data, to evaluate their appropriate uses and the claims that might be made from them. There are also different methodological proposals to define a social media data quality framework to use as a sample. This session offers the opportunity to address the violence issue from different perspectives; with their contributions, the speakers will focus on the different aspects of the approaches and their strengths and weaknesses. This session's main aim is to discuss potential links between “official” and “trusted smart statistics” in finding new and more appropriate ways to study GBV.

Organiser: Ms Claudia Villante

Speaker: Francesca Grum

Speaker: Michael Slyuzberg

Speaker: Adrian Franco Barrios

Speaker: Maria Giuseppina Muratore 

Discussant: Lucilla Scarnicchia