The Janus Face of New Media Propaganda: The Case of Patani Neojihadist YouTube Warfare and Its Islamophobic Effect on Cyber-Actors

Andre, Virginie

doi:10.1080/09596410.2014.900948

Cited by 13 publications

(5 citation statements)

References 5 publications

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“…For example, in Thailand there is evidence of reactionary Buddhist extremism in response to a perception of the danger posed by Islam and Muslims (Beech 2013). A Buddhist culture, confronted with the spectre of so-called jihadi terrorism, responds with forms of violent behaviour that, prima facie, run counter to predominant religious teachings and sensibilities (Andre 2012(Andre , 2014. But such a paradoxical shift from a religious predilection for peace to a religiously sanctioned reaction of violence is not so uncommon.…”

Section: Introductionmentioning

confidence: 93%

Islamophobia as Reactive Co-Radicalization

Pratt

2015

Islam and Christian–Muslim Relations

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Section: Introductionmentioning

confidence: 93%

Islamophobia as Reactive Co-Radicalization

Pratt

2015

Islam and Christian–Muslim Relations

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“…In [ 2 , 3 ], different machine learning strategies were proposed that were aimed at detecting radicalization efforts, cyber-recruitment, hate promotion and extremist support in a variety of online platforms, including YouTube, Twitter and Tumblr. According to [ 6 ], the broadcasting of insurgent atrocities over the Internet on platforms such as YouTube increases the spectacle effect of extreme violence by ensuring that it reaches wider audiences. The authors of [ 59 ] compared radical discourse between North Caucasus and Uyghur neo-jihadist narratives on the creation of collective identities and found that the narratives have similar features, which can be identified in a set of sub-narratives.…”

Section: Youtube and Analyticsmentioning

confidence: 99%

Net activism and whistleblowing on YouTube: a text mining analysis

Turenne

2022

Multimed Tools Appl

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Social media is more and more dominant in everyday life for people around the world. YouTube content is a resource that may be useful, in social computational science, for understanding key questions about society. Using this resource, we performed web scraping to create a dataset of 644,575 video transcriptions concerning net activism and whistleblowing. We automatically performed linguistic feature extraction to capture a representation of each video using its title, description and transcription (downloaded metadata). The next step was to clean the dataset using automatic clustering with linguistic representation to identify unmatched videos and noisy keywords. Using these keywords to exclude videos, we finally obtained a dataset that was reduced by 95%, i.e., it contained 35,730 video transcriptions. Then, we again automatically clustered the videos using a lexical representation and split the dataset into subsets, leading to hundreds of clusters that we interpreted manually to identify a hierarchy of topics of interest concerning whistleblowing. We used the dataset to learn a lexical representation for a specific topic and to detect unknown whistleblowing videos for this topic; the accuracy of this detection is 57.4%. We also used the dataset to identify interesting context linguistic markers around the names of whistleblowers. From a given list of names, we automatically extracted all 5-g word sequences from the dataset and identified interesting markers in the left and right contexts for each name by manual interpretation. The results of our study are the following: a dataset (raw and cleaned collections) concerning whistleblowing, a hierarchy of topics about whistleblowing, the automatic prediction of whistleblowing and the semi-automatic semantic analysis of markers around whistleblower names. This text mining analysis can be exploited for digital sociology and e-democracy studies.

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“…Thai security forces have scrutinized some Islamic educational institutions because some insurgents have used schools as clandestine points of recruitment. Continuing insurgent acts and violence targeting Buddhists and negative media coverage have contributed to suspicion of Islamic schools in Thailand, and growing anti-Muslim sentiment (Andre 2014). At the same time, Thai government financial support and efforts to improve connections with Islamic private schools is a valuable means to improve educational outcomes for youth throughout the region (Liow 2009).…”

Section: Context Of Study Populationmentioning

confidence: 99%

Perceptions of Human Security among Islamic School Students, Parents and Teachers in Southern Thailand’s Subnational Conflict Zone

Abdel-Monem

Sateemae

et al. 2020

Civil Wars

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Since 2004, close to 7,000 people have died in Thailand's domestic insurgency in its three Muslim-majority southern provinces, one of the longestrunning, low-intensity conflicts in Southeast Asia. This study assesses perceptions of human security threats in the area among a sample of students, their parents, and teachers of Islamic private schools (n = 427, n = 331, n = 51, respectively), and how they relate to perceptions of government actors and other community institutions. Questionnaire items were drawn from the World Values Survey Wave 6. Focus groups and interviews were also conducted to deepen our understanding of conflict related dynamics. digitalcommons.unl.edu

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The Janus Face of New Media Propaganda: The Case of Patani Neojihadist YouTube Warfare and Its Islamophobic Effect on Cyber-Actors

Cited by 13 publications

References 5 publications

Islamophobia as Reactive Co-Radicalization

Islamophobia as Reactive Co-Radicalization

Net activism and whistleblowing on YouTube: a text mining analysis

Perceptions of Human Security among Islamic School Students, Parents and Teachers in Southern Thailand’s Subnational Conflict Zone

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