The Conversation around Islam on Twitter: Topic Modeling and Sentiment Analysis of Tweets about the Muslim Community in Spain since 2015

Abstract

Social media, especially Twitter, has become a platform where hate, toxic, intolerant, and discriminatory speech is increasingly spread. These messages are aimed at different vulnerable social groups, due to some of their differentiating characteristics with respect to the dominant one, whether they are phenotypic, religious, cultural, gender, sexual, etc. Of all these minorities, one of the most affected is the Muslim community, especially since the beginning of the Mediterranean refugee crisis, during which migration from the Middle East and North Africa increased considerably. Spain does not escape this reality as, given its proximity to Morocco, it is one of the main destinations for migrants from North Africa. In this context, there are already several studies focused on specifically investigating Islamophobic speech disseminated on social platforms, normally focused on specific cases. However, there are still no studies focused on analyzing the entire conversation around Islam and the Muslim community that takes place on Twitter and in a southern European country such as Spain, aiming to identify the latent sentiments and the main underlying topics and their characteristics, which would help to relativize and dimension the relevance of Islamophobic messages, as well as to analyze them from a more solid base. The main objective of the present study is to identify the most frequent words, the main underlying topics, and the latent sentiments that predominate in the general conversation about Islam and the Muslim community on Twitter in Spain and in Spanish during the last 8 years. To do this, 190,320 messages that included keywords related to Muslim culture and religion were collected and analyzed using computational techniques. The findings show that the most frequent words in these messages were mostly descriptive and not derogatory, and the predominant latent topics were mostly neutral and informative, although two of them could be considered reliable indicators of Islamophobic rejection. Similarly, while the overall average sentiment in this conversation trended negatively, neutral and positive messages were more prevalent. However, in the negative messages, the sentiment was considerably more pronounced.