Social media and terrorism discourse: the Islamic State’s (IS) social media discursive content and practices

KhosraviNik, Majid; Amer, Mohammedwesam

doi:10.1080/17405904.2020.1835684

Cited by 20 publications

(10 citation statements)

References 19 publications

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“…In all, the current study focuses on assessing communication structures and identifying leading voices based on the fact that a wide array of communicating actors dynamically curate the flow of content on social media (Anspach, 2017;Thorson and Wells, 2016). Information curation by various actors diverges from traditional linear flows of content from mass media (producers) to ordinary persons (consumers) (KhosraviNik et al, 2016). In line with this argument, the curated flow framework suggests that various actors in a networked environment simultaneously engage in shaping the content flow by producing, selecting, filtering or framing the content (Thorson and Wells, 2016).…”

Section: Curated Flows and Networked Gatekeepingmentioning

confidence: 99%

Section: Curated Flows and Networked Gatekeepingmentioning

confidence: 99%

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Taking the lead in misinformation-related conversations in social media networks during a mass shooting crisis

Lee

Britt

Kanthawala

2022

INTR

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PurposeMisinformation (i.e. information identified as false) spreads widely and quickly on social media – a space where crowds of ordinary citizens can become leading voices – during a crisis when information is in short supply. Using the theoretical lenses of socially curated flow and networked gatekeeping frameworks, we address the following three aims: First, we identify emergent opinion leaders in misinformation-related conversations on social media. Second, we explore distinct groups that contribute to online discourses about misinformation. Lastly, we investigate the actual dominance of misinformation within disparate groups in the early phases of mass shooting crises.Design/methodology/approachThis paper used network and cluster analyses of Twitter data that focused on the four most prevalent misinformation themes surrounding the El Paso mass shooting.FindingsA total of seven clusters of users emerged, which were classified into five categories: (1) boundary-spanning hubs, (2) broadly popular individuals, (3) reputation-building hubs, (4) locally popular individuals and (5) non-opinion leaders. Additionally, a content analysis of 128 tweets in six clusters, excluding the cluster of non-opinion leaders, further demonstrated that the opinion leaders heavily focused on reiterating and propagating misinformation (102 out of 128 tweets) and collectively made zero corrective tweets.Originality/valueThese findings expand the intellectual understanding of how various types of opinion leaders can shape the flow of (mis)information in a crisis. Importantly, this study provides new insights into the role of trans-boundary opinion leaders in creating an echo chamber of misinformation by serving as bridges between otherwise fragmented discourses.

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Section: Curated Flows and Networked Gatekeepingmentioning

confidence: 99%

Section: Curated Flows and Networked Gatekeepingmentioning

confidence: 99%

Taking the lead in misinformation-related conversations in social media networks during a mass shooting crisis

Lee

Britt

Kanthawala

2022

INTR

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“…Menurut Fairclough dan Wodak (Khosravinik & Amer, 2020) titik berat dalam analisis wacana melihat dari bahasa sebagai praktik kekuasaan dan dalam literatur CDA, wacana sebagai praktik menyiratkan hubungan dialektis antara peristiwa diskursif tertentu dan situasi, institusi, dan struktur sosial, yang membingkainya. Sedangkan, DeFleur dan Sandra Ball (Y. Ahmadi, 2020) wacana dalam suatu berita tidak sekedar mencerminkan realitas akan tetapi dapat menciptakan realitas, hal tersebut menunjukkan bahwa media massa memiliki pengaruh besar terhadap pemahaman masyarakat dalam menyikapi sebuah realitas.…”

Section: Kajian Teoriunclassified

Analisis Wacana Kritis Pembicaraan di Twitter terkait Topik Patung Naga di Bandara Internasional Yogyakarta

Sanubarianto¹

2022

ETNO

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Pembicaraan tentang patung naga di Bandara Internasional Yogyakarta sempat mengemuka di Twitter. Bahasan yang terjadi pun berkutat seputar wacana sosial-budaya sampai pada politik. Topik ini semakin menghangat karena diangkat oleh Mustofa Nahrawardaya, yang secara politis, berseberangan. Penelitian ini berupaya mengungkapkan dimensi tekstual, praktik wacana, dan praktik sosial-budaya pada pembicaraan topik tersebut. Untuk mendapatkannya, metode yang digunakan adalah analisis wacana kritis model Norman Fairclough. Hasil dari penelitian ini menunjukkan bahwa secara dimensi tekstual pembahasan tentang patung naga semula berawal dari pertanyaan yang direspons beragam. Namun, dari sisi praktik wacana, melihat latar belakang siapa yang memulai topik, pembicaraan yang semula memiliki konteks budaya berubah menjadi konteks politik. Pada akhirnya, melihat respons-respons yang bermunculan, dari sisi sosial budaya, tampaklah bahwa pembicaraan tersebut mengarah ke politik identitas.

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“…In addition to this, the digital practices and discourses of the Islamic State when exploiting social media communication environments to propagate their jihadist ideology and mobilize specific audiences have been examined by a group of authors [30]. To counter and examine the Islamic State of Iraq and Syria (ISIS) recruitment behavior through social media Kibtiah and co-workers [31] suggest text mining methods be deployed, that categorize text document into specific categories and help to make tracing network more efficient.…”

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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Social media and terrorism discourse: the Islamic State’s (IS) social media discursive content and practices

Cited by 20 publications

References 19 publications

Taking the lead in misinformation-related conversations in social media networks during a mass shooting crisis

Taking the lead in misinformation-related conversations in social media networks during a mass shooting crisis

Analisis Wacana Kritis Pembicaraan di Twitter terkait Topik Patung Naga di Bandara Internasional Yogyakarta

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

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