Telegramming Hate: Far Right Themes on the Dark Social Media

2021 ◽  
Vol 46 (4) ◽  
Author(s):  
Ahmed Al-Rawi

Background: This study empirically examines the multimodal discourses of far-right groups on mobile apps. Many fringe groups find Telegram a convenient platform to spread hate speech without the need to censor their content or fear being blocked from the platform.  Analysis: This study collected all the posts from 15 far-right Telegram channels. The data was analyzed using a mixed-method approach, including an examination of profile images, hashtags, mentions, and emojis that have been weaponized to assist in hate dissemination.  Conclusion and implications: The findings show that one major theme on Telegram revolves around white peoples’ perceived grievances and discussions on conservatism followed by the minorities as the problem. Contexte : Contexte Cette étude examine empiriquement les discours multimodaux des groupes d’extrême droite sur les applications mobiles. De nombreux groupes marginaux trouvent Telegram une plate-forme pratique pour diffuser leurs messages haineux sans avoir besoin de censurer leur contenu ou de penser qu’ils pourraient être bloqués sur la plate-forme. Analyse : J’ai collecté tous les messages de 15 chaînes Telegram d’extrême droite. Pour analyser les données, j’ai utilisé une approche de méthode mixte comprenant un examen des images de profil, des hashtags, des mentions et des emojis qui ont tous été militarisés pour aider à la diffusion de la haine. Conclusion et implications : Les résultats montrent qu’un thème majeur tourne autour des griefs perçus des Blancs et des discussions sur le conservatisme suivi par les minorités comme problème.

2017 ◽  
Vol 7 (1) ◽  
pp. 13-22 ◽  
Author(s):  
Uttam Chakraborty ◽  
Savita Bhat

Rapid growth of online social media reduces the marketer’s control over brand management. Consumers share their brand-related experiences (through online reviews) in various online social media platforms. It is a major challenge for the marketers to understand the effects of online reviews on a brand’s image. This study addresses the issue and attempts to understand the effects of online reviews on brand image. The concept of brand image is broken up into two parts, namely, functional and hedonic. The study follows a mixed method approach using both quantitative and qualitative techniques. Quantitative techniques have been used to measure the objective experiences of the consumers, whereas qualitative techniques have been used to examine the subjective experiences of the consumers. For quantitative technique, structural equation modelling (SEM) has been adopted to determine the relationships between the variables. For qualitative technique, netnography has been followed. Quantitative data analysis reveals that online credible reviews have more significant effect on hedonic brand image. Qualitative study also shows evidences of functional and hedonic brand images in online community. Future directions for research are mentioned as well.


2017 ◽  
Vol 29 (1) ◽  
pp. 530-550 ◽  
Author(s):  
M. Claudia tom Dieck ◽  
Timothy Hyungsoo Jung ◽  
Woo Gon Kim ◽  
Yunji Moon

Purpose This paper aims to propose and test a modified technology acceptance model for the social media networks (SMNs) in the luxury hotel context, integrating satisfaction and continued usage intention, using a mixed-method approach. SMNs have revolutionized the way people communicate, search for information and share experiences. The technology acceptance model is the predominant theory for researching technology acceptance; however, there is a gap in identifying and testing context-specific constructs. Design/methodology/approach This paper uses a mixed-method approach. The researchers conducted 16 interviews and 258 questionnaires with luxury hotel guests. Following the collection of data, interviews and questionnaires were analyzed using thematic and partial least square analysis. Findings Findings show that accessibility, trust, social influence and perceived benefits influence perceived ease of use and perceived usefulness, which affect attitude and satisfaction and ultimately continued usage intentions. Findings also reveal that enjoyment, although qualitatively proposed, does not influence luxury hotel guests’ SMNs continued usage intention. Practical implications This study suggests that hotel managers have to concentrate their marketing efforts in enhancing SMN’s interaction and increasing the number of positive reviews to retain current customers and acquire new ones. Hotels should also develop effective mobile strategies by adopting mobile social network webs and applications, as accessibility becomes more important in today’s marketplace. Originality/value Former scholars adopted the approach of proposing external dimensions based on previous research and, thus, did not integrate up-to-date and context-specific variables. Therefore, the present paper uses a new approach by exploring SMN-specific dimensions and testing them in the luxury hotel context.


2021 ◽  
Vol 30 (1) ◽  
Author(s):  
Rose Marie Santini ◽  
Débora Salles ◽  
Charbelly Estrella Estrella ◽  
Carlos Eduardo Barros ◽  
Daniela Orofino

Social bots are automated agents programmed to act on social media impersonating human behaviour to influence discussions online. This paper aims to contribute to the discussion of how bots can endanger online communication and alter information flows. We resorted to a mixed-method approach based on grounded theory and observational techniques in order to investigate the bots’ activities online during the 2016 municipal elections in Rio de Janeiro. We collected related content on Twitter in this period and detected 3,101 bots. This sample was classified in three categories based on tweeting content: user-generated bot, media spambot, and political bot. Our findings indicate that, although bots work for different political and social purposes, their computational nature claims into service of dominant social groups and economical elites. We conclude that computational propaganda is building a dangerous scenario of widespread automation in which different kinds of algorithms bias social media conversation.


2015 ◽  
Vol 25 (3) ◽  
pp. 568-583 ◽  
Author(s):  
Hing Kai Chan ◽  
Xiaojun Wang ◽  
Ewelina Lacka ◽  
Min Zhang

2018 ◽  
Vol 2 (1) ◽  
pp. 5-16
Author(s):  
Syed Gohar Abbas ◽  
◽  
Jalil Ahmed ◽  
Zainab Fakhr

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