Social Media

In recent years, there has been an intensification of international extremist violence linked in varying degrees to Internet-facilitated radicalisation. This has related to, among other things, a growth in prevalence of politically violent actors, including far-right and jihadist collectives. Extreme political polarisation, sometimes termed the ‘hyper-tribalism’ of those with violent or extreme views, is to ...

The present paper contributes to the research on the activities of far-right actors on social media by examining the interconnections between far-right actors and groups on Telegram platform using network analysis. The far-right network observed on Telegram is highly decentralized, similarly to the far-right networks found on other social media platforms. The network is divided ...

Hate speech and toxic communication online is on the rise. Responses to this issue tend to offer technical (automated) or non-technical (human content moderation) solutions, or see hate speech as a natural product of hateful people. In contrast, this article begins by recognizing platforms as designed environments that support particular practices while discouraging others. In ...

This report examines the social media shutdown in the wake of the Easter Attacks in Sri Lanka, and its impacts on journalists and post-incident communal violence. By highlighting the shutdown’s limitations, social costs and impact on misinformation, this report presents key recommendations for policy-makers, journalists and other key stakeholders. This report is part of a ...

This study focuses on the role of Internet memes in the communication of two far-right groups in Finland. The material consists of 426 memes posted by Finland First and the Soldiers of Odin between the years 2015 and 2017 on Facebook. Multimodal discourse analysis was applied to understand the contents, forms, and rhetorical functions communicated ...

This paper presents a survey on hate speech detection. Given the steadily growing body of social media content, the amount of online hate speech is also increasing. Due to the massive scale of the web, methods that automatically detect hate speech are required. Our survey describes key areas that have been explored to automatically recognize ...

Online social media platforms generally attempt to mitigate hateful expressions, as these comments can be detrimental to the health of the community. However, automatically identifying hateful comments can be challenging. We manually label 5,143 hateful expressions posted to YouTube and Facebook videos among a dataset of 137,098 comments from an online news media. We then ...

The increasing presence of hate speech on social media has drawn significant investment from governments, companies, and empirical research. Existing methods typically use a supervised text classification approach that depends on carefully engineered features. However, it is unclear if these features contribute equally to the performance of such methods. We conduct a feature selection analysis ...

Social media has become an indispensable part of the everyday lives of millions of people around the world. It provides a platform for expressing opinions and beliefs, communicated to a massive audience. However, this ease with which people can express themselves has also allowed for the large scale spread of propaganda and hate speech. To ...

Hate speech may take different forms in online social media. Most of the investigations in the literature are focused on detecting abusive language in discussions about ethnicity, religion, gender identity and sexual orientation. In this paper, we address the problem of automatic detection and categorization of misogynous language in online social media. The main contribution ...