scholarly journals The Datafication of Hate: Expectations and Challenges in Automated Hate Speech Monitoring

2020 ◽  
Vol 3 ◽  
Author(s):  
Salla-Maaria Laaksonen ◽  
Jesse Haapoja ◽  
Teemu Kinnunen ◽  
Matti Nelimarkka ◽  
Reeta Pöyhtäri
Keyword(s):  
Hate Speech ◽  
Speech Monitoring

Clinical Success Using the Audio-Visual Feedback Training for Cluttering

2019 ◽  
Vol 4 (6) ◽  
pp. 1589-1594
Author(s):  
Yvonne van Zaalen ◽  
Isabella Reichel
Keyword(s):  
Visual Feedback ◽  
Clinical Success ◽  
Pause Duration ◽  
Digital Audio ◽  
Male Adolescents ◽  
Feedback Training ◽  
Positive Effects ◽  
Speech Monitoring ◽  
Adolescents And Adults

Purpose Among the best strategies to address inadequate speech monitoring skills and other parameters of communication in people with cluttering (PWC) is the relatively new but very promising auditory–visual feedback (AVF) training ( van Zaalen & Reichel, 2015 ). This study examines the effects of AVF training on articulatory accuracy, pause duration, frequency, and type of disfluencies of PWC, as well as on the emotional and cognitive aspects that may be present in clients with this communication disorder ( Reichel, 2010 ; van Zaalen & Reichel, 2015 ). Methods In this study, 12 male adolescents and adults—6 with phonological and 6 with syntactic cluttering—were provided with weekly AVF training for 12 weeks, with a 3-month follow-up. Data was gathered on baseline (T0), Week 6 (T1), Week 12 (T2), and after follow-up (T3). Spontaneous speech was recorded and analyzed by using digital audio-recording and speech analysis software known as Praat ( Boersma & Weenink, 2017 ). Results The results of this study indicated that PWC demonstrated significant improvements in articulatory rate measurements and in pause duration following the AVF training. In addition, the PWC in the study reported positive effects on their ability to retell a story and to speak in more complete sentences. PWC felt better about formulating their ideas and were more satisfied with their interactions with people around them. Conclusions The AVF training was found to be an effective approach for improving monitoring skills of PWC with both quantitative and qualitative benefits in the behavioral, cognitive, emotional, and social domains of communication.

Letter to Mark Zuckerberg on Hate Speech

2020 ◽  
Author(s):  
Arthur C. Evans
Keyword(s):  
Hate Speech

Exploring the assessment of hate speech and other complaints by the BCCSA

2007 ◽  
Vol 28 (1-2) ◽  
pp. 30-55
Author(s):  
L. Venter
Keyword(s):  
Hate Speech

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.

A Study on Online Hate Speech and Offline Hate Speech Relationship

2019 ◽  
Vol 15 (2) ◽  
pp. 23-36
Author(s):  
Je Seong Cho ◽  
Youn oh Cho
Keyword(s):  
Hate Speech

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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