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相关论文: Tackling Online Abuse: A Survey of Automated Abuse…

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Abuse on the Internet is an important societal problem of our time. Millions of Internet users face harassment, racism, personal attacks, and other types of abuse across various platforms. The psychological effects of abuse on individuals…

计算与语言 · 计算机科学 2021-04-15 Pushkar Mishra , Helen Yannakoudakis , Ekaterina Shutova

The pervasiveness of abusive content on the internet can lead to severe psychological and physical harm. Significant effort in Natural Language Processing (NLP) research has been devoted to addressing this problem through abusive content…

计算与语言 · 计算机科学 2021-07-23 Svetlana Kiritchenko , Isar Nejadgholi , Kathleen C. Fraser

Online abusive behavior affects millions and the NLP community has attempted to mitigate this problem by developing technologies to detect abuse. However, current methods have largely focused on a narrow definition of abuse to detriment of…

社会与信息网络 · 计算机科学 2019-06-11 David Jurgens , Eshwar Chandrasekharan , Libby Hemphill

The rise of online communication platforms has been accompanied by some undesirable effects, such as the proliferation of aggressive and abusive behaviour online. Aiming to tackle this problem, the natural language processing (NLP)…

计算与语言 · 计算机科学 2020-05-29 Santhosh Rajamanickam , Pushkar Mishra , Helen Yannakoudakis , Ekaterina Shutova

The proliferation of abusive language in online communications has posed significant risks to the health and wellbeing of individuals and communities. The growing concern regarding online abuse and its consequences necessitates methods for…

计算与语言 · 计算机科学 2025-04-25 Samaneh Hosseini Moghaddam , Kelly Lyons , Cheryl Regehr , Vivek Goel , Kaitlyn Regehr

The success of social media platforms has facilitated the emergence of various forms of online abuse within digital communities. This abuse manifests in multiple ways, including hate speech, cyberbullying, emotional abuse, grooming, and…

计算与语言 · 计算机科学 2025-07-03 Jose A. Diaz-Garcia , Joao Paulo Carvalho

To support safety and inclusion in online communications, significant efforts in NLP research have been put towards addressing the problem of abusive content detection, commonly defined as a supervised classification task. The research…

计算与语言 · 计算机科学 2020-10-29 Svetlana Kiritchenko , Isar Nejadgholi

Hate speech is increasingly prevalent online, and its negative outcomes include increased prejudice, extremism, and even offline hate crime. Automatic detection of online hate speech can help us to better understand these impacts. However,…

计算与语言 · 计算机科学 2021-02-10 John D Gallacher

The rise of social media platforms has led to an increase in cyber-aggressive behavior, encompassing a broad spectrum of hostile behavior, including cyberbullying, online harassment, and the dissemination of offensive and hate speech. These…

计算与语言 · 计算机科学 2024-12-31 Swapnil Mane , Suman Kundu , Rajesh Sharma

Cyberbullying has been a significant challenge in the digital era world, given the huge number of people, especially adolescents, who use social media platforms to communicate and share information. Some individuals exploit these platforms…

计算机与社会 · 计算机科学 2026-04-07 Adamu Gaston Philipo , Doreen Sebastian Sarwatt , Jianguo Ding , Mahmoud Daneshmand , Huansheng Ning

The prevalence of offensive content on the internet, encompassing hate speech and cyberbullying, is a pervasive issue worldwide. Consequently, it has garnered significant attention from the machine learning (ML) and natural language…

计算与语言 · 计算机科学 2024-07-29 Alphaeus Dmonte , Tejas Arya , Tharindu Ranasinghe , Marcos Zampieri

Online toxic content has grown into a pervasive phenomenon, intensifying during times of crisis, elections, and social unrest. A significant amount of research has been focused on detecting or analyzing toxic content using machine-learning…

计算与语言 · 计算机科学 2025-09-19 Gautam Kishore Shahi , Tim A. Majchrzak

Abuse on the Internet represents a significant societal problem of our time. Previous research on automated abusive language detection in Twitter has shown that community-based profiling of users is a promising technique for this task.…

计算与语言 · 计算机科学 2019-04-09 Pushkar Mishra , Marco Del Tredici , Helen Yannakoudakis , Ekaterina Shutova

Online abuse is becoming an increasingly prevalent issue in modern-day society, with 41 percent of Americans having experienced online harassment in some capacity in 2021. People who identify as women, in particular, can be subjected to a…

人机交互 · 计算机科学 2023-01-19 Sarah Barrington

Hate speech, offensive language, sexism, racism and other types of abusive behavior have become a common phenomenon in many online social media platforms. In recent years, such diverse abusive behaviors have been manifesting with increased…

While extensive popularity of online social media platforms has made information dissemination faster, it has also resulted in widespread online abuse of different types like hate speech, offensive language, sexist and racist opinions, etc.…

Technological advancements have resulted in an exponential increase in the use of online social networks (OSNs) worldwide. While online social networks provide a great communication medium, they also increase the user's exposure to…

计算机与社会 · 计算机科学 2024-01-09 Sylvia W Azumah , Nelly Elsayed , Zag ElSayed , Murat Ozer

Online abuse has grown increasingly complex, spanning toxic language, harassment, manipulation, and fraudulent behavior. Traditional machine-learning approaches dependent on static classifiers and labor-intensive labeling struggle to keep…

计算与语言 · 计算机科学 2026-04-02 Suraj Kath , Sanket Badhe , Preet Shah , Ashwin Sampathkumar , Shivani Gupta

The use of abusive language online has become an increasingly pervasive problem that damages both individuals and society, with effects ranging from psychological harm right through to escalation to real-life violence and even death.…

计算与语言 · 计算机科学 2023-09-26 Mali Jin , Yida Mu , Diana Maynard , Kalina Bontcheva

The proliferation of harmful content on online platforms is a major societal problem, which comes in many different forms including hate speech, offensive language, bullying and harassment, misinformation, spam, violence, graphic content,…

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