Italian web debate about immigration

Abstract

[EN] Social media websites can be used as a data source for mining public opinion on a variety of subjects including immigration. Twitter, in particular, allows for the evaluation of public opinion across time. In this study, a large dataset of Italian tweets between 2018 and 2022 containing a set of keywords related to immigration is analysed using text mining techniques such as topic modelling and word embedding techniques. The volume time series is compared with Google trends and shows a good correlation. In particular some topic modelling clusters are directly related to observed peaks of volumes across time, but also summarize more general patterms. Word embedding representation provide an accurate representation of specific words and themes. The joint use of these techniques provide coherent insights about the overall debate complementing each other by enriching current statistics with useful auxiliary information.