Regulating terrorist content on social media: automation and the rule of law

Macdonald, Stuart; Correia, Sara; Watkin, Amy-Louise

doi:10.1017/s1744552319000119

Cited by 30 publications

(20 citation statements)

References 29 publications

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“…However, not all levels of online interaction are created equal. In recent years, there have been a number of studies which discuss terrorists' utilization of end-to-end encrypted platforms, particularly as they have been pushed away from mainstream social media sites (Conway et al, 2018;Macdonald, Correia, & Watkin, 2019). These platforms offer a higher level of operational security and, by their nature, are not compliant to subpoena.…”

Section: Online Activity As An Impediment To Successmentioning

confidence: 99%

The online behaviors of Islamic state terrorists in the United States

Whittaker

2021

Criminology & Public Policy

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This study offers an empirical insight into terrorists' use of the Internet. Although criminology has previously been quiet on this topic, behavior-based studies can aid in understanding the interactions between terrorists and their environments. Using a database of 231 US-based Islamic State terrorists, four important findings are offered: (1) This cohort utilized the Internet heavily for the purposes of both networking with co-ideologues and learning about their intended activity. (2) There is little reason to believe that these online interactions are replacing offline ones, as has previously been suggested. Rather, terrorists tend to operate in both domains. (3) Online activity seems to be similar across the sample, regardless of the number of co-offenders or the sophistication of attack. (4) There is reason to believe that using the Internet may be an impediment to terrorists' success. Policy Implications: The findings of this study have two important policy implications. First, it is vital to understand the multiplicity of environments in which terrorists inhabit. Policy makers have tended to emphasize the online domain as particularly dangerous and ripe for exploitation. While this is understandable from one perspective, simplistic and monocausal explanations for radicalization must be avoided. Terrorists operate in both the online and offline domain and there is

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Section: Online Activity As An Impediment To Successmentioning

confidence: 99%

The online behaviors of Islamic state terrorists in the United States

Whittaker

2021

Criminology & Public Policy

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“…The results indicate that the textual models using vector embedding features significantly improve the detection over TF-IDF features [35]. Stuart and others [15] highlight the displacement effects that result from the automated removal and blocking of terrorist content and suggest that regard must be implemented to the whole social-media ecology covering jihadist groups other than the so-called Islamic State and other forms of violent extremist organizations. Since rule by law is only a necessary and not a sufficient, condition for compliance with rule-of-law values, the study examines two further sets of issues including the clarity with which social media companies define terrorist content and the adequacy of the processes by which a user may appeal against an account suspension or the blocking or removal of content.…”

Section: Related Workmentioning

confidence: 91%

“…The challenges related to the domains of sentiment analysis and text classification are widely studied in the literature [15], [14]. Shah et al create a multilingual sentiment lexicon with intensity weights to classify social media contents as high extreme, low extreme, moderate, and neutral.…”

Section: Related Workmentioning

confidence: 99%

Adaptable Reduced-Complexity Approach Based on State Vector Machine for Identification of Criminal Activists on Social Media

et al. 2021

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In today's world, the security agencies has an emerging challenge to identify and counter the malicious contents spread on the social media by the terrorists. However, the text classification techniques have limitations like text visualization, pre-processing, features extraction, and larger features space. The objectives of the criminal users also change with time causing the learning models with additional tasking of identifying the altered malicious textual contents. In this paper, a simplified yet adaptable framework is proposed that makes use of a novel features extraction algorithm (FEA) for extracting features from the textual part of social media contents. It extracts a Boolean feature vector of only 8 dimensions, from each textual content in six steps. The first two values of each feature vector contains information about the presence of URL of malicious contents in the text, the next two values convey their hashtag campaign, 5-6th and 7-8th values are related to their sympathetic and hate campaigns respectively. The extracted features are suitably used to train the state vector machine for the classification of the malicious content promulgated by the criminals. The performance of the proposed method is evaluated against other popular feature selection/ extraction algorithms like TF-IDF Information Gain (IG), Gini Index (GI), Chi Square statistics and PCA and machine learning classifiers like Decision Tree (DT), Random Forest (RF), and Naïve Bayes (NB). It is found that the proposed approach consumes less energy on text visualization, pre-processing, and dimensionality reduction. It also reduces the time-space complexity of the features extraction process and is capable to steer according to the changing future strategies of the active criminal groups.The proposed approach is found to effectively analyze the propaganda material publish by the extremists. It automatically identifies the radical text on social media platforms allowing understanding of the behaviors characteristics and subsequent blockage of such content.

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“…In 23 months, starting from August 2015, Twitter suspended about a million accounts for promoting violence (Fernandez et al, 2018;Singh et al, 2018). In the latter half of 2017, YouTube deleted 150,000 videos spreading violence and extremism and about half of these videos were removed within 2 h of being uploaded (Macdonald, 2018;Macdonald et al, 2019).…”

Section: Artificial Intelligence (Ai)mentioning

confidence: 99%

Countering violent extremism using social media and preventing implementable strategies for Bangladesh

Barua

Kafy

2021

Heliyon

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Globally, more than 85% of youth use social media daily in the medium of Facebook, Youtube, Twitter, etc., which is more than 70% for Bangladesh. The young population of Bangladesh is rapidly embracing social media through the internet and afflicted with the malaise of countering violent extremism (CVE), often through Facebook. Given the increasing connectedness that the internet and social media offer, it is crucial that the fight against CVE shift to the digital space. Extremists are increasingly adopting novel ways and means based on technology to draw unsuspecting youth to their cause. It is essential to establish effective implementable strategies to stop the CVE activities using social media in Bangladesh. This study aims to identify existing initiatives globally in the space of disruptive online technologies that have yielded some success in preventing CVE. Various publications such as journal and news articles, TV news, and blogs have been used as data sources for this study. Also, fifteen expert interviews have been conducted to identify the most effective strategies for CVE in Bangladesh. Through the content analysis, the study highlights successful efforts and explores technology-based initiatives that can be deployed in Bangladesh to minimize the impact of VE activities through online technology. Finally, recommendations for strategies to restrict VE activities through technologies have been suggested that can be potentially implemented by the Bangladesh government by coordinating with international donor agencies and CVE practitioners. The research output recommends that Bangladesh and other less developed countries can concurrently deal with CVE by successfully using cutting-edge online/digital technologies.

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Regulating terrorist content on social media: automation and the rule of law

Cited by 30 publications

References 29 publications

The online behaviors of Islamic state terrorists in the United States

The online behaviors of Islamic state terrorists in the United States

Adaptable Reduced-Complexity Approach Based on State Vector Machine for Identification of Criminal Activists on Social Media

Countering violent extremism using social media and preventing implementable strategies for Bangladesh

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