No abstract

The present study analyzed the differences in the language usage between pro-ISIS users and random users on Twitter. Based on the literature, it was expected that, when comparing the tweets from both samples, distinctive patterns would be found on their usage of similar linguistic categories. This observational study compared a dataset of 105 pro-ISIS users with 91 random Twitter users, both collected between 2015 and 2016. The Linguistic Inquiry Word Count (LIWC) software was employed to analyze the terminology used by both groups from a quantitative perspective. Relevant LIWC categories used in previous studies were included in the assessment. ISIS supporters used significantly more third person plural pronouns and less first person singular and second person pronouns. They also used more words related with death, certainty, and anger than the random group, along with more words containing six letters or more. Finally, more negative language and tone was used by the pro-ISIS group. The language used by ISIS supporters on Twitter was discussed, as well as comparisons to relevant studies on other political extremists. Ultimately, our results suggest that broad similarities in language usage exist between ISIS supporters and other extreme ideologies.

The alt-right is a far-right movement that has uniquely developed on social media, before becoming prominent in the 2016 United States presidential elections. However, very little research exists about their discourse and organization online. This study aimed to analyze how a sample of alt-right supporters organized themselves in the week before and after the 2018 midterm elections in the US, along with which topics they most frequently discussed. Using community finding and topic extraction algorithms, results indicated that the sample commonly used racist language and antiimmigration themes, criticised mainstream media and advocated for alternative media sources, whilst also engaging in discussion of current news stories. A subsection of alt-right supporters were found to focus heavily on white supremacist themes. Furthermore, small groups of alt-right supporters discussed anime, technology and religion. These results supported previous results from studies investigating the discourse of alt-right supporters.

Extremism has grown as a global problem for society in recent years, especially after the apparition of movements such as jihadism. This and other extremist groups have taken advantage of different approaches, such as the use of Social Media, to spread their ideology, promote their acts and recruit followers. The extremist discourse, therefore, is reflected on the language used by these groups. Natural language processing (NLP) provides a way of detecting this type of content, and several authors make use of it to describe and discriminate the discourse held by these groups, with the final objective of detecting and preventing its spread. Following this approach, this survey aims to review the contributions of NLP to the field of extremism research, providing the reader with a comprehensive picture of the state of the art of this research area. The content includes a first conceptualization of the term extremism, the elements that compose an extremist discourse and the differences with other terms. After that, a review description and comparison of the frequently used NLP techniques is presented, including how they were applied, the insights they provided, the most frequently used NLP software tools, descriptive and classification applications, and the availability of datasets and data sources for research. Finally, research questions are approached and answered with highlights from the review, while future trends, challenges and directions derived from these highlights are suggested towards stimulating further research in this exciting research area.

Political tensions have grown throughout Europe since the beginning of the new century. The consecutive crises led to the rise of different social movements in several countries, in which the political status quo changed. These changes included an increment of the different tensions underlying politics, as has been reported after many other political and economical crises during the twentieth century. This article proposes the study of the political discourse, and its underlying tension, during Madrid’s elections (Spain) in May 2021 by using a mixed approach . To demonstrate if an aggressive tone is used during the campaign, a mixed methodology approach is applied: quantitative computational techniques, related to natural language processing, are used to conduct a first general analysis of the information screened; then, these methods are used for detecting specific trends that can be later filtered and analyzed using a qualitative approach (content analysis), which is also conducted to extract insights about the information found. The main outcomes of this study show that the electoral campaign is not as negative as perceived by the citizens and that there was no relationship between the tone of the discourse and its dissemination. The analysis confirms that the most ideologically extreme parties tend to have a more aggressive language than the moderate ones. The content analysis carried out using our methodology showed that Twitter is used as a sentiment thermometer more than as a way of communicating concrete politics.