Tweeting Islamophobia

<p>The great promise of social media platforms such as Twitter is to connect people separated across time and space. This has had far-ranging consequences for politics by changing discursive, participative and organisational practices. However, despite much early techno-optimism about platform...

पूर्ण विवरण

ग्रंथसूची विवरण
मुख्य लेखक: Vidgen, B
अन्य लेखक: Yasseri, T
स्वरूप: थीसिस
भाषा:English
प्रकाशित: 2019
विषय:
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author Vidgen, B
author2 Yasseri, T
author_facet Yasseri, T
Vidgen, B
author_sort Vidgen, B
collection OXFORD
description <p>The great promise of social media platforms such as Twitter is to connect people separated across time and space. This has had far-ranging consequences for politics by changing discursive, participative and organisational practices. However, despite much early techno-optimism about platforms like Twitter, concerns are growing that they enable harmful, hateful and divisive behaviours. In this thesis, I focus on one of the most concerning and harmful behaviours on Twitter and in politics more broadly: Islamophobic hate speech. The socio-political consequences of hate speech are deeply concerning, and include causing harm to targeted victims, spreading divisiveness, and normalizing dangerous and extremist ideas.</p> <p>The aim of this thesis is to enhance our understanding of the nature and dynamics of Islamophobic hate speech amongst followers of UK political parties on Twitter. I study four parties from across the political spectrum: the BNP, UKIP, the Conservatives and Labour. I make three main contributions. First, I define Islamophobia in terms of negativity and generality, thus making a robust, theoretically-informed contribution to the study of a deeply contested concept. This argument informs the second contribution, which is methodological: I create a multi-class supervised machine learning classifier for Islamophobic hate speech. This distinguishes between weak and strong varieties and can be applied robustly and at scale. </p> <p>My third contribution is theoretical. Drawing together my substantive findings, I argue that Islamophobic tweeting amongst followers of UK parties can be characterised as a wind system which contains Islamophobic <em>hurricanes</em>. This analogy captures the complex, heterogeneous dynamics underpinning Islamophobia on Twitter, and highlights its devastating effects. I also show that Islamist terrorist attacks drive Islamophobia, and that this affects followers of all four parties studied here. I use this finding to extend the theory of cumulative extremism beyond extremist groups to include individuals with mainstream affiliations. These contributions feed into ongoing academic, policymaking and activist discussions about Islamophobic hate speech in both social media and UK politics.</p>
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spelling oxford-uuid:3c32d29d-e2e4-4913-abf8-2a28886f55a72024-12-07T15:22:14ZTweeting IslamophobiaThesishttp://purl.org/coar/resource_type/c_db06uuid:3c32d29d-e2e4-4913-abf8-2a28886f55a7internet studiesonline politicssocial sciencepolitical scienceEnglishORA Deposit2019Vidgen, BYasseri, TMargetts, H<p>The great promise of social media platforms such as Twitter is to connect people separated across time and space. This has had far-ranging consequences for politics by changing discursive, participative and organisational practices. However, despite much early techno-optimism about platforms like Twitter, concerns are growing that they enable harmful, hateful and divisive behaviours. In this thesis, I focus on one of the most concerning and harmful behaviours on Twitter and in politics more broadly: Islamophobic hate speech. The socio-political consequences of hate speech are deeply concerning, and include causing harm to targeted victims, spreading divisiveness, and normalizing dangerous and extremist ideas.</p> <p>The aim of this thesis is to enhance our understanding of the nature and dynamics of Islamophobic hate speech amongst followers of UK political parties on Twitter. I study four parties from across the political spectrum: the BNP, UKIP, the Conservatives and Labour. I make three main contributions. First, I define Islamophobia in terms of negativity and generality, thus making a robust, theoretically-informed contribution to the study of a deeply contested concept. This argument informs the second contribution, which is methodological: I create a multi-class supervised machine learning classifier for Islamophobic hate speech. This distinguishes between weak and strong varieties and can be applied robustly and at scale. </p> <p>My third contribution is theoretical. Drawing together my substantive findings, I argue that Islamophobic tweeting amongst followers of UK parties can be characterised as a wind system which contains Islamophobic <em>hurricanes</em>. This analogy captures the complex, heterogeneous dynamics underpinning Islamophobia on Twitter, and highlights its devastating effects. I also show that Islamist terrorist attacks drive Islamophobia, and that this affects followers of all four parties studied here. I use this finding to extend the theory of cumulative extremism beyond extremist groups to include individuals with mainstream affiliations. These contributions feed into ongoing academic, policymaking and activist discussions about Islamophobic hate speech in both social media and UK politics.</p>
spellingShingle internet studies
online politics
social science
political science
Vidgen, B
Tweeting Islamophobia
title Tweeting Islamophobia
title_full Tweeting Islamophobia
title_fullStr Tweeting Islamophobia
title_full_unstemmed Tweeting Islamophobia
title_short Tweeting Islamophobia
title_sort tweeting islamophobia
topic internet studies
online politics
social science
political science
work_keys_str_mv AT vidgenb tweetingislamophobia