scholarly journals DETECTION OF HATE SPEECH IN SOCIAL NETWORKS: A SURVEY ON MULTILINGUAL CORPUS

2019 ◽  
Author(s):  
Areej Al-Hassan ◽  
Hmood Al-Dossari
Keyword(s):  
Social Networks ◽  
Hate Speech ◽  
Multilingual Corpus

scholarly journals Misinformation, Radicalization and Hate Through the Lens of Users

2020 ◽  
Author(s):  
Manoel Horta Ribeiro ◽  
Virgílio A. F. Almeida ◽  
Wagner Meira Jr
Keyword(s):  
Social Networks ◽  
Case Studies ◽  
Network Structure ◽  
Online Social Networks ◽  
Hate Speech ◽  
Far Right ◽  
Content Creation ◽  
Political Opinion

The popularization of Online Social Networks has changed the dynamics of content creation and consumption. In this setting, society has witnessed an amplification in phenomena such as misinformation and hate speech. This dissertation studies these issues through the lens of users. In three case studies in social networks, we: (i) provide insight on how the perception of what is misinformation is altered by political opinion; (ii) propose a methodology to study hate speech on a user-level, showing that the network structure of users can improve the detection of the phenomenon; (iii) characterize user radicalization in far-right channels on YouTube through time, showing a growing migration towards the consumption of extreme content in the platform.

scholarly journals Offensive Comments in the Brazilian Web: a dataset and baseline results

2017 ◽  
Author(s):  
Rogers Prates De Pelle ◽  
Viviane P. Moreira
Keyword(s):  
Social Networks ◽  
Supervised Classification ◽  
Hate Speech ◽  
Daily Basis ◽  
Online Media ◽  
Classification Algorithms ◽  
Web Content ◽  
Massive Number ◽  
Standard Classification ◽  
Future Work

Brazilian Web users are among the most active in social networks and very keen on interacting with others. Offensive comments, known as hate speech, have been plaguing online media and originating a number of lawsuits against companies which publish Web content. Given the massive number of user generated text published on a daily basis, manually filtering offensive comments becomes infeasible. The identification of offensive comments can be treated as a supervised classification task. In order to obtain a model to classify comments, an annotated dataset containing positive and negative examples is necessary. The lack of such a dataset in Portuguese, limits the development of detection approaches for this language. In this paper, we describe how we created annotated datasets of offensive comments for Portuguese by collecting news comments on the Brazilian Web. In addition, we provide classification results achieved by standard classification algorithms on these datasets which can serve as baseline for future work on this topic.

scholarly journals Morally Homogeneous Networks and Radicalism

2021 ◽  
pp. 194855062110593
Author(s):  
Mohammad Atari ◽  
Aida Mostafazadeh Davani ◽  
Drew Kogon ◽  
Brendan Kennedy ◽  
Nripsuta Ani Saxena ◽  
...  
Keyword(s):  
Social Networks ◽  
Hate Speech ◽  
Right Wing ◽  
Real Group ◽  
The World

Online radicalization is among the most vexing challenges the world faces today. Here, we demonstrate that homogeneity in moral concerns results in increased levels of radical intentions. In Study 1, we find that in Gab—a right-wing extremist network—the degree of moral convergence within a cluster predicts the number of hate-speech messages members post. In Study 2, we replicate this observation in another extremist network, Incels. In Studies 3 to 5 ( N = 1,431), we demonstrate that experimentally leading people to believe that others in their hypothetical or real group share their moral views increases their radical intentions as well as willingness to fight and die for the group. Our findings highlight the role of moral convergence in radicalization, emphasizing the need for diversity of moral worldviews within social networks.

Poland

2018 ◽  
Author(s):  
Robert Gorwa
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Hate Speech ◽  
Public Life ◽  
Digital Tools ◽  
Social Media Marketing ◽  
Fake News ◽  
Political Campaign ◽  
Marketing Firms ◽  
Digital Politics

This chapter provides the first overview of political bots, fake accounts, and other false amplifiers in Poland. Based on extensive interviews with political campaign managers, journalists, activists, employees of social media marketing firms, and civil society groups, the chapter outlines the emergence of Polish digital politics, covering the energetic and hyper-partisan “troll wars,” the interaction of hate speech with modern platform algorithms, and the recent effects of “fake news” and various sources of apparent Russian disinformation. The chapter then explores the production and management of artificial identities on Facebook, Twitter, and other social networks—an industry confirmed to be active in Poland—and assesses how they can be deployed for both political and commercial purposes. Overall, the chapter provides evidence for a rich array of digital tools that are increasingly being used by various actors to exert influence over Polish politics and public life.

scholarly journals Hate speech on social networks and traditional media in Republic of N. Macedonia

2020 ◽  
Vol 8 (3) ◽  
pp. 82-90
Author(s):  
Andon Majhosev ◽  
Jadranka Denkova ◽  
Shenaj Osmanov
Keyword(s):  
Social Networks ◽  
Hate Speech ◽  
Traditional Media

scholarly journals Hate Speech Detection in Portuguese with Naïve Bayes, SVM, MLP and Logistic Regression

2020 ◽  
Author(s):  
Adriano Silva ◽  
Norton Roman
Keyword(s):  
Machine Learning ◽  
Social Networks ◽  
Logistic Regression ◽  
Hate Speech ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Machine Learning Algorithms ◽  
Speech Detection ◽  
Related Literature ◽  
Automatic Methods

Even though social networks can provide free space for discussing ideas, people can also use them to propagate hate speech and, given the amount of written material in such networks, it becomes necessary to rely on automatic methods for identifying this problem. In this work, we set out to verify the use of some classic Machine Learning algorithms for the task of hate speech detection in tweets written in Portuguese, by testing four different models (SVM, MLP, Logistic Regression and Naïve Bayes) with different configurations. Results show that these algorithms produce better results (in terms of micro-averaged F1 score) than the LSTM used for benchmark, being also competitive to other results by the related literature

scholarly journals CYBERCULTURE AND HATE SPEECH: A CASE STUDY ABOUT THE POLICIES AGAINST HATE SPEECH LEAD BY THE COUNCIL OF EUROPE

2021 ◽  
Vol 6 (6) ◽  
Author(s):  
Luís Cardoso ◽  
Ana Catarina Bruno
Keyword(s):  
Social Networks ◽  
Literature Review ◽  
Hate Speech ◽  
Theoretical Framework ◽  
Council Of Europe ◽  
Art Analysis ◽  
Definition Of ◽  
State Of Art

Social networks are interactive platforms developed to facilitate relations and exchanges of information between people who share the same interests, experiences and opinions (Recuero, 2009). The main goal of this study is to know the definition of cyberculture and cyberspace and understand the phenomenon of hate speech on social networks. The theoretical framework of the article is about the understanding of cyberculture and cyberspace, the evolution of social networks and the definition of hate speech and its targets. Finally, a case study is carried on the combat policies against hate speech lead by the Council of Europe. The methodology will include state of art analysis, literature review and the observation of the Council of Europe website. <p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/edu_01/0810/a.php" alt="Hit counter" /></p>

Sign in / Sign up

Export Citation Format

Share Document