The Perceptions About the Immigration Phenomenon Communicated Through Social Media Platforms in Italy

The paper focuses on the analysis of the perceptions of immigration in Italy expressed through Twitter. More specifically we aim to identify the main words through which Twitter users talk about migration and migrants in the last decade by highlighting changes over time; to analyse relations between words in the same period; to detect sentiment and emotions expressed by tweets and retweets always verifying changes and persisting views over the years. We apply text mining and sentiment analysis techniques to a database of tweets and retweets in the Italian language published in the period 2011-2020 containing hashtags and keywords related to migration. Text mining converts texts into analyzable structured data while sentiment analysis has the objective of checking whether a sentence expresses a positive, negative or neutral sentiment. Our work confirms that part of the debate regarding migration on social media is linked to specific aspects of the migration phenomenon in Italy and it is strongly polarised. In the last decade, references to arrivals by sea have always been present in the social debate. The importance of the role of politicians or institutional figures is confirmed by our analysis. From the sentiment analysis emerged a gradual shift, most pronounced in the last year, towards a slight predominance of words associated with negative emotions, particularly fear. Our analysis confirms the need of training stakeholders on migration complexities, spreading accurate information through mainstream media, fostering informed social media discussions, promoting cross-cultural interactions, analyzing social perceptions, and implementing policies to reduce stereotypes.