scholarly journals Ethical and technical challenges of AI in tackling hate speech

2021 ◽  
Vol 29 ◽  
Author(s):  
Diogo Cortiz ◽  
Arkaitz Zubiaga
Keyword(s):  
Social Media ◽  
Large Scale ◽  
Information Overload ◽  
Scientific Literature ◽  
Hate Speech ◽  
Freedom Of Expression ◽  
Speech Detection ◽  
Detection Algorithms ◽  
Technical Challenges

In this paper, we discuss some of the ethical and technical challenges of using Artificial Intelligence for online content moderation. As a case study, we used an AI model developed to detect hate speech on social networks, a concept for which varying definitions are given in the scientific literature and consensus is lacking. We argue that while AI can play a central role in dealing with information overload on social media, it could cause risks of violating freedom of expression (if the project is not well conducted). We present some ethical and technical challenges involved in the entire pipeline of an AI project - from data collection to model evaluation - that hinder the large-scale use of hate speech detection algorithms. Finally, we argue that AI can assist with the detection of hate speech in social media, provided that the final judgment about the content has to be made through a process with human involvement.

scholarly journals Time of Your Hate: The Challenge of Time in Hate Speech Detection on Social Media

2020 ◽  
Vol 10 (12) ◽  
pp. 4180 ◽  
Author(s):  
Komal Florio ◽  
Valerio Basile ◽  
Marco Polignano ◽  
Pierpaolo Basile ◽  
Viviana Patti
Keyword(s):  
Social Media ◽  
Hate Speech ◽  
Time Window ◽  
Classification Performance ◽  
Fine Tuning ◽  
Classification Model ◽  
Temporal Distance ◽  
Speech Detection ◽  
Highly Sensitive

The availability of large annotated corpora from social media and the development of powerful classification approaches have contributed in an unprecedented way to tackle the challenge of monitoring users’ opinions and sentiments in online social platforms across time. Such linguistic data are strongly affected by events and topic discourse, and this aspect is crucial when detecting phenomena such as hate speech, especially from a diachronic perspective. We address this challenge by focusing on a real case study: the “Contro l’odio” platform for monitoring hate speech against immigrants in the Italian Twittersphere. We explored the temporal robustness of a BERT model for Italian (AlBERTo), the current benchmark on non-diachronic detection settings. We tested different training strategies to evaluate how the classification performance is affected by adding more data temporally distant from the test set and hence potentially different in terms of topic and language use. Our analysis points out the limits that a supervised classification model encounters on data that are heavily influenced by events. Our results show how AlBERTo is highly sensitive to the temporal distance of the fine-tuning set. However, with an adequate time window, the performance increases, while requiring less annotated data than a traditional classifier.

scholarly journals Hate Speeches on Twitter and Facebook in South Asia: A Case Study Of Malala Yousufzai

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Saba Naz, Dr. Muhammad Osama Shafiq
Keyword(s):  
Social Media ◽  
South Asia ◽  
Quantitative Research ◽  
Large Scale ◽  
Hate Speech ◽  
Radical Change ◽  
Quantitative Research Methods ◽  
Social Media Platforms ◽  
Media Platform

Nowadays social media platforms have become a medium that allows people to post anything they wish. Since the time internet grew, a radical change has been discerned in society. With the emergence of social media sites, many challenges also thrived in the society that took the society into interesting and alarming ways altogether. As time is passing as technology is intensifying new forms of hate, abuse, bullying, and discrimination are also increasing in society. It can be said that digital technology is reshaping coercion based on caste, color, gender, race, culture, likes, dislikes. Many societies are concerned with this problem of growing hate speeches on social media but no proper barrier on these sites has been seen to prevent hate discourses. This study examined the attitudes of social media users including Facebook and Twitter over the incident of Noble Prize laureate Malala Yousufzai, a young activist who worked and spoke for the educational rights of girls who were born in Swat valley. She spoke against this erroneous system that didn’t allow girls to gain education and became a prominent member of society at the little age of 14. She was shot by Taliban and then a controversy started against her, some people admired her and she became a celebrity all over South Asia while an extreme amount of criticism was also seen against her incident. Through this study, we aim to understand the abundance of hate speech on Facebook and Twitter in South Asia by using Qualitative and Quantitative Research Methods. For that purpose we took the case study method and provide a large-scale measurement and analysis of different hashtags used during the case of Malala on the social media platform. To achieve the objective of our research, we amassed Tweets and Facebook posts posted since the year 2011 till now related to this case. This article identifies numerous forms of hate speeches on social media that are arising in South Asia and altering the minds of people using social media, it is also guiding how to abate hate speeches that are delivered on social media with particular hashtags on various incidents and matters. The collected data revealed that hate speech has become a social problem with substantial inimical effects in societies. This study explains that social media should be utilized to benefit mankind positively and gently.

scholarly journals Social Media in and Around a Temporary Large-Scale Refugee Shelter in the Netherlands

2021 ◽  
Vol 7 (2) ◽  
pp. 205630512110249
Author(s):  
Peer Smets ◽  
Younes Younes ◽  
Marinka Dohmen ◽  
Kees Boersma ◽  
Lenie Brouwer
Keyword(s):  
Social Media ◽  
The Netherlands ◽  
Crisis Communication ◽  
Asylum Seekers ◽  
Large Scale ◽  
State Policies ◽  
Refugee Crisis ◽  
Top Down ◽  
And Migration

During the 2015 refugee crisis in Europe, temporary refugee shelters arose in the Netherlands to shelter the large influx of asylum seekers. The largest shelter was located in the eastern part of the country. This shelter, where tents housed nearly 3,000 asylum seekers, was managed with a firm top-down approach. However, many residents of the shelter—mainly Syrians and Eritreans—developed horizontal relations with the local receiving society, using social media to establish contact and exchange services and goods. This case study shows how various types of crisis communication played a role and how the different worlds came together. Connectivity is discussed in relation to inclusion, based on resilient (non-)humanitarian approaches that link society with social media. Moreover, we argue that the refugee crisis can be better understood by looking through the lens of connectivity, practices, and migration infrastructure instead of focusing only on state policies.

scholarly journals A Web Interface for Analyzing Hate Speech

2021 ◽  
Vol 13 (3) ◽  
pp. 80
Author(s):  
Lazaros Vrysis ◽  
Nikolaos Vryzas ◽  
Rigas Kotsakis ◽  
Theodora Saridou ◽  
Maria Matsiola ◽  
...  
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Graphical User Interface ◽  
Hate Speech ◽  
Web Interface ◽  
Learning Models ◽  
Speech Detection ◽  
Media Services ◽  
The Web ◽  
Machine Learning Models

Social media services make it possible for an increasing number of people to express their opinion publicly. In this context, large amounts of hateful comments are published daily. The PHARM project aims at monitoring and modeling hate speech against refugees and migrants in Greece, Italy, and Spain. In this direction, a web interface for the creation and the query of a multi-source database containing hate speech-related content is implemented and evaluated. The selected sources include Twitter, YouTube, and Facebook comments and posts, as well as comments and articles from a selected list of websites. The interface allows users to search in the existing database, scrape social media using keywords, annotate records through a dedicated platform and contribute new content to the database. Furthermore, the functionality for hate speech detection and sentiment analysis of texts is provided, making use of novel methods and machine learning models. The interface can be accessed online with a graphical user interface compatible with modern internet browsers. For the evaluation of the interface, a multifactor questionnaire was formulated, targeting to record the users’ opinions about the web interface and the corresponding functionality.

scholarly journals Online Multilingual Hate Speech Detection: Experimenting with Hindi and English Social Media

2020 ◽  
Author(s):  
Neeraj Vashistha ◽  
Arkaitz Zubiaga
Keyword(s):  
Social Media ◽  
Hate Speech ◽  
Model Performance ◽  
Academic Community ◽  
Human Interaction ◽  
Superior Performance ◽  
Competitive Performance ◽  
Speech Detection ◽  
Improve Model ◽  
Use Of The Internet

The exponential increase in the use of the Internet and social media over the last two decades has changed human interaction. This has led to many positive outcomes, but at the same time it has brought risks and harms. While the volume of harmful content online, such as hate speech, is not manageable by humans, interest in the academic community to investigate automated means for hate speech detection has increased. In this study, we analyse six publicly available datasets by combining them into a single homogeneous dataset and classify them into three classes, abusive, hateful or neither. We create a baseline model and we improve model performance scores using various optimisation techniques. After attaining a competitive performance score, we create a tool which identifies and scores a page with effective metric in near-real time and uses the same as feedback to re-train our model. We prove the competitive performance of our multilingual model on two langauges, English and Hindi, leading to comparable or superior performance to most monolingual models.

scholarly journals Terrorist Speech under Bills C-51 and C-59 and the Othman Hamdan Case: The Continued Incoherence of Canada’s Approach

2019 ◽  
pp. 203
Author(s):  
Kent Roach
Keyword(s):  
Social Media ◽  
Hate Speech ◽  
Criminal Code ◽  
Immigration Law ◽  
The Internet ◽  
Media Companies ◽  
Violent Extremism ◽  
Fundamental Freedoms

It is argued that neither the approach taken to terrorist speech in Bill C-51 nor Bill C-59 is satisfactory. A case study of the Othman Hamdan case, including his calls on the Internet for “lone wolves” “swiftly to activate,” is featured, along with the use of immigration law after his acquittal for counselling murder and other crimes. Hamdan’s acquittal suggests that the new Bill C-59 terrorist speech offence and take-down powers based on counselling terrorism offences without specifying a particular terrorism offence may not reach Hamdan’s Internet postings. One coherent response would be to repeal terrorist speech offences while making greater use of court-ordered take-downs of speech on the Internet and programs to counter violent extremism. Another coherent response would be to criminalize the promotion and advocacy of terrorist activities (as opposed to terrorist offences in general in Bill C-51 or terrorism offences without identifying a specific terrorist offence in Bill C-59) and provide for defences designed to protect fundamental freedoms such as those under section 319(3) of the Criminal Code that apply to hate speech. Unfortunately, neither Bill C-51 nor Bill C-59 pursues either of these options. The result is that speech such as Hamdan’s will continue to be subject to the vagaries of take-downs by social media companies and immigration law.

scholarly journals USE OF CYBER HATE IN THE ELECTORAL CAMPAIGNS BY THE MAINSTREAM POLITICAL PARTIES OF PAKISTAN

2021 ◽  
Vol 9 (2) ◽  
pp. 325-332
Author(s):  
Ayesha Siddiqua
Keyword(s):  
Social Media ◽  
Discourse Analysis ◽  
Political Parties ◽  
Hate Speech ◽  
Freedom Of Expression ◽  
Qualitative Interviews ◽  
The Political ◽  
Electoral Campaigns ◽  
General Elections ◽  
Cyber Ethics

Purpose of the study: The purpose of the study is to examine the use of cyber hate by the Pakistan’s mainstream political parties. The issue of poll rigging in Pakistan’s General Elections 2013 is examined through discourse analysis of the related tweets. The study also aims at comprehending the extent to which cyber ethics were violated during the digital electoral campaigns. Methodology: Discourse Analysis of the tweets generated from the official Twitter handles of PTI and PMLN leaders was conducted to examine the use of cyber hate by the Pakistan’s mainstream political parties. Violation of cyber ethics was explored through the qualitative interviews of 8 purposively selected social media managers of PMLN, PPP, and PTI. Main Findings: The findings indicated that party leadership/politicians used the elements of cyber hate which included abusive language, provocation, and character assassination against their opponents during the digital electoral campaign in general and regarding the poll rigging issue of Pakistan’s General Elections 2013 in specific. Resultantly the tweets using strong adjectives and metaphors on the political opponents were more frequently re-tweeted and attracted more favorites. Applications of this study: The study can be helpful in various cross-disciplinary areas that focus on the examination of the usage and impact of social media and cyberspace as a medium for hate speech dissemination. The study can significantly contribute to areas related to cyber ethics, digital electoral campaigning, freedom of expression, and political opinion building. Novelty/Originality of this study: The study’s originality lies in its attempt to unfold the foundations of digital electoral campaigning in Pakistan and how cyberhate was used as a pivotal tool for advancing the political narratives in a fragile democratic society.

Debunking Intermediary Censorship Framework in Social Media via a Content Retrieval and Classification Software

2017 ◽  
pp. 169-195
Author(s):  
Baramee Navanopparatskul ◽  
Sukree Sinthupinyo ◽  
Pirongrong Ramasoota
Keyword(s):  
Social Media ◽  
Service Providers ◽  
Freedom Of Expression ◽  
Business Organizations ◽  
Governmental Agencies ◽  
Online Discussion Forum ◽  
Content Retrieval ◽  
Intermediary Liability ◽  
Online Service Providers

Following the enactment of computer crime law in Thailand, online service providers are compelled to control illegal content including content that is deemed harmful or problematic. This situation leads to self-censorship of intermediaries, often resulting in overblocking to avoid violating the law. Such filtering flaw both infringes users' freedom of expression and impedes the business of OSPs in Thailand. The Innovative Retrieval System (IRS) is thus developed to investigate intermediary censorship in online discussion forum, Pantip.com, as a case study of social media. The result shows that there is no consistency of censorship pattern on the website at all. The censorship criteria depend on type of content in each forum. Overblocking is also high, over 70% of removed content, due to intimidation of governmental agencies, lawsuits from business organizations, and fear of intermediary liability. Website administrator admitted that he would cut off some users to avoid business troubles.

18. Freedom of Expression

2017 ◽  
Author(s):  
Bernadette Rainey ◽  
Elizabeth Wicks ◽  
Andclare Ovey
Keyword(s):  
Social Media ◽  
Human Rights ◽  
Hate Speech ◽  
Freedom Of Expression ◽  
Case Law ◽  
European Convention ◽  
Free Expression ◽  
The Internet

This chapter examines the protection of the freedom of expression in the European Convention on Human Rights, discusses the provisions of Article 10, and explains that the majority of cases concerning Article 10 are brought by persons who have received some penalty for defaming or insulting other people. It analyses what constitutes an interference with free expression and considers the limitations on freedom of expression. The chapter also examines the judgments made by the Strasbourg Court on several related cases, including those that involved incitement to violence and hate speech, obscenity, and blasphemy. It also covers the development of case-law concerning social media and the internet.

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