Online Library

Advancements in big data analytics offer new avenues for the analysis and deciphering of suspicious activities on the internet. One promising new technology to increase the identification of terrorism threats is based on probabilistic computing. The technology promises to provide more efficient problem solutions in encryption and cybersecurity. Probabilistic computing technologies use large amounts of data, though, which raises potential privacy concerns. A study (N = 1,023) was conducted to survey public support for using probabilistic computing technologies to increase counterterrorism efforts. Overall, strong support was found for the use of publicly available personal information (e.g., personal websites). Regarding private personal information (e.g., online conversations), respondents perceived it to be more appropriate to use information from out-group members (non-American citizens) than from in-group members (American citizens). In line with a social-identity account, this form of in-group favoritism was strongest among respondents displaying a combination of strong national identities and strong privacy concerns.

Die Autoren nehmen sich des Problems der Nutzung des Internets durch Linksextremisten an und analysieren die unterschiedlichen “Gesichter“ des linksextremismus im Internet.

The article describes a systematic approach used by the Swiss Intelligence Service (SAP). The procedure described is illustrated by the authentic case of messages among extremists going on the Website www.islamic-minbar.com, a case that was prosecuted and brought to verdict by the Attorney General of the Swiss Confederation.

The prevalence of dangerous misinformation and extreme views online has intensified since the onset of Israel-Hamas war on 7 October 2023. Social media platforms have long grappled with the challenge of providing effective mitigation schemes that can scale to the 5 billion-strong online population. Here, we introduce a novel solution grounded in online network engineering and demonstrate its potential through small pilot studies. We begin by outlining the characteristics of the online social network infrastructure that have rendered previous approaches to mitigating extremes ineffective. We then present our new online engineering scheme and explain how it circumvents these issues. The efficacy of this scheme is demonstrated through a pilot empirical study, which reveals that automatically assembling groups of users online with diverse opinions, guided by a map of the online social media infrastructure, and facilitating their anonymous interactions, can lead to a softening of extreme views. We then employ computer simulations to explore the potential for implementing this scheme online at scale and in an automated manner, without necessitating the contentious removal of specific communities, imposing censorship, relying on preventative messaging, or requiring consensus within the online groups. These pilot studies provide preliminary insights into the effectiveness and feasibility of this approach in online social media settings.

This article investigates Twitter data related to the kidnapping case of two German nationals in the southern region of the Philippines by the Abu Sayyaf Group (ASG). It explores perceptions of the ASG, along with associated organizations and sentiments indicated in the tweets together with statistically significant relationships. Findings revealed that: “Rebel” and “Militant” were the most frequently used labels for the ASG; a majority of the tweets contained sentiments that assess threats such as abduction and kidnapping of hostages; and almost half contained words that indicate negotiation or concession to the demands of the captors. Logistic regression analyses on “Rebel” and “Islamist” revealed positive coefficients for these sentiments used as predictors. This meant that people who assessed threats and expressed sentiments that responders should concede to the captors’ demands were more likely to use the “Rebel” or “Islamist” labels. Rather than the two longstanding dominant narratives of the ASG as terrorists and criminals, the emerging rebel and militant labels suggest a more domestically and politically sensitive Twitter commentary than is represented in the work of the Al-Qaeda-centric paradigm exponents. These findings, along with the complex associated political and policy contexts and implications, are discussed in this article.