Hate Speech in Political Election

2021 ◽  
Vol 32 (1) ◽  
pp. 113-137
Author(s):  
Sung Soo Hong
Keyword(s):  
Hate Speech ◽  
Political Election

scholarly journals Narasi Ujaran Kebencian dalam Pemilihan Umum Kepala Daerah (PILKADA)

2019 ◽  
Vol 39 (2) ◽  
pp. 166
Author(s):  
Najahan Musyafak ◽  
Ahmad Hasan Asy'ari Ulama'i
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Hate Speech ◽  
Public Officials ◽  
Party Leaders ◽  
Social Media Platform ◽  
Media Platform ◽  
The Government ◽  
Political Election

<p><em>Hate speech on social media has become a theme of discussion in various forms of discourse in society. This paper focuses on expressions of hate speech related to regional political election uploaded through posts from personal and group accounts on the Facebook social media platform from January to July 2018. This study uses content analysis by adopting Soesilo's six hate speech criteria. The results of the study showed that the forms of hate speech on Facebook were expressed in the form of photos, drawings, illustrations, memes, and words that had the connotation of provocation, insults, and incitement. Hate speech comes from personal and group accounts, addressed to individuals, public officials such as presidents, party leaders, and the government.</em></p><p><em><br /></em></p><p>Ujaran kebencian di media sosial telah menjadi tema pembahasan dalam berbagai bentuk wacana di masyarakat. Tulisan ini fokus pada ekspresi ujaran kebencian yang terkait dengan masalah Pemilihan Kepala Daerah yang diunggah melalui postingan dari akun personal maupun kelompok dalam platform media sosial <em>facebook</em> selama Januari sampai bulan Juli 2018. Studi ini menggunakan analisis isi dengan mengadopsi enam kriteria ujaran kebencian Soesilo. Hasil studi menunjukkan bahwa bentuk ujaran kebencian di <em>facebook </em>diungkapkan dalam bentuk foto, gambar, ilustrasi, meme, dan kata-kata yang memiliki konotasi provokasi, penghinaan, dan hasutan. Ujaran kebencian bersumber dari akun pribadi dan kelompok, ditujukan kepada individu, pejabat publik seperti presiden, ketua partai, dan pemerintah.</p><p><em><br /></em></p>

The Roma in Post-Communist Bulgaria: Growing Social Marginalization and State Policies

2020 ◽  
Vol 2 (1) ◽  
pp. 1-24
Author(s):  
Yorgos Christidis
Keyword(s):  
Political Parties ◽  
Social Exclusion ◽  
Hate Crime ◽  
Hate Speech ◽  
Poor Performance ◽  
State Policies ◽  
Social Marginalization ◽  
Popular Support ◽  
Economic Problems ◽  
The Poor

This article analyzes the growing impoverishment and marginalization of the Roma in Bulgarian society and the evolution of Bulgaria’s post-1989 policies towards the Roma. It examines the results of the policies so far and the reasons behind the “poor performance” of the policies implemented. It is believed that Post-communist Bulgaria has successfully re-integrated the ethnic Turkish minority given both the assimilation campaign carried out against it in the 1980s and the tragic events that took place in ex-Yugoslavia in the 1990s. This Bulgaria’s successful “ethnic model”, however, has failed to include the Roma. The “Roma issue” has emerged as one of the most serious and intractable ones facing Bulgaria since 1990. A growing part of its population has been living in circumstances of poverty and marginalization that seem only to deteriorate as years go by. State policies that have been introduced since 1999 have failed at large to produce tangible results and to reverse the socio-economic marginalization of the Roma: discrimination, poverty, and social exclusion continue to be the norm. NGOs point out to the fact that many of the measures that have been announced have not been properly implemented, and that legislation existing to tackle discrimination, hate crime, and hate speech is not implemented. Bulgaria’s political parties are averse in dealing with the Roma issue. Policies addressing the socio-economic problems of the Roma, including hate speech and crime, do not enjoy popular support and are seen as politically damaging.

Pembelajaran Integrasi tentang Etika Penggunaan Media Sosial dalam Materi Ajar Pendidikan Agama Islam di Sekolah Menangah Atas

2019 ◽  
Vol 3 (1) ◽  
pp. 72
Author(s):  
Irfan Afandi
Keyword(s):  
Social Media ◽  
Industrial Revolution ◽  
Hate Speech ◽  
Islamic Education ◽  
Learning Models ◽  
Negative Effects ◽  
Education Material ◽  
Use Of Social Media ◽  
The Waves ◽  
Critical Reason

The humanitarian problem in the development of the industrial revolution 4.0 is very complex and is at the stage of worrying. No human being separated from the effect of the waves. High school is active users (user) of the results of the industrial revolution the 4.0. The problem that arises in the use of social media including the demise of expertise, the dissemination of hate speech and fabricated news. Teaching Islamic education material should be able to respond to this by providing normative information in the Qur'an and Hadith so that students can escape from its negative effects. One of the solutions offered was to integrate these materials with integratsi learning models in the themes that have been arranged in the school's learning policy. Integrating this material must through the phases between the awarding phase of learning, information or materials to grow a critical reason, generate hypotheses and generalities.

Effectiveness of Supervised Classification Models for Hate Speech on Twitter

2020 ◽  
Author(s):  
Kunal Srivastava ◽  
Ryan Tabrizi ◽  
Ayaan Rahim ◽  
Lauryn Nakamitsu
Keyword(s):  
Supervised Classification ◽  
Hate Speech ◽  
The Internet ◽  
Classification Models ◽  
Personal Attack ◽  
Political Beliefs ◽  
The Many ◽  
Primary Medium ◽  
Offensive Speech

<div> <div> <div> <p>Abstract </p> <p>The ceaseless connectivity imposed by the internet has made many vulnerable to offensive comments, be it their physical appearance, political beliefs, or religion. Some define hate speech as any kind of personal attack on one’s identity or beliefs. Of the many sites that grant the ability to spread such offensive speech, Twitter has arguably become the primary medium for individuals and groups to spread these hurtful comments. Such comments typically fail to be detected by Twitter’s anti-hate system and can linger online for hours before finally being taken down. Through sentiment analysis, this algorithm is able to distinguish hate speech effectively through the classification of sentiment. </p> </div> </div> </div>

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