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Countering hate on social media: Large scale classification of hate and counter speech [article]

Joshua Garland and Keyan Ghazi-Zahedi and Jean-Gabriel Young and Laurent Hébert-Dufresne and Mirta Galesic
2020 arXiv   pre-print
Altogether, our results highlight the potential of automated methods to evaluate the impact of coordinated counter speech in stabilizing conversations on social media.  ...  One major obstacle to researching this question is a lack of large labeled data sets for training automated classifiers to identify counter speech.  ...  Acknowledgments The authors would like to thank Will Tracy and Santa Fe Institute's Applied Complexity team for support and resources throughout this project.  ... 
arXiv:2006.01974v3 fatcat:jswpkuu3fvhgxaaquz7qx24rbu

Towards countering hate speech and personal attack in social media [article]

Polychronis Charitidis, Stavros Doropoulos, Stavros Vologiannidis, Ioannis Papastergiou, Sophia Karakeva
2019 arXiv   pre-print
The damaging effects of hate speech in social media are evident during the last few years, and several organizations, researchers and the social media platforms themselves have tried to harness them without  ...  However, it is apparent that such approaches depend on large-scale datasets in order to exhibit competitive performance.  ...  Our primary goal was to provide large scale datasets in order to contribute to the improvement of methods for identifying hateful and offensive content on social media.  ... 
arXiv:1912.04106v1 fatcat:xip53vjtinazpfi64fqiory4dy

Countering hate on social media: Large scale classification of hate and counter speech

Joshua Garland, Keyan Ghazi-Zahedi, Jean-Gabriel Young, Laurent Hébert-Dufresne, Mirta Galesic
2020 Proceedings of the Fourth Workshop on Online Abuse and Harms   unpublished
Altogether, our results highlight the potential of automated methods to evaluate the impact of coordinated counter speech in stabilizing conversations on social media. ⇤ Denotes equal contribution.  ...  One major obstacle to researching this question is a lack of large labeled data sets for training automated classifiers to identify counter speech.  ...  J.G. was partially supported by an Omidyar and an Ap-  ... 
doi:10.18653/v1/2020.alw-1.13 fatcat:qvpgandry5fnxjdg4tcofsa5yq

Counter Hate Speech in Social Media: A Survey [article]

Dana Alsagheer, Hadi Mansourifar, Weidong Shi
2022 arXiv   pre-print
With the high prevalence of offensive language against minorities in social media, counter-hate speeches (CHS) generation is considered an automatic way of tackling this challenge.  ...  The CHS generation is based on the optimistic assumption that any attempt to intervene the hate speech in social media can play a positive role in this context.  ...  ACKNOWLEDGMENT This research is supported by University of Houston President's Grants to Enhance Research on Racism (2020).  ... 
arXiv:2203.03584v1 fatcat:zpu3qnpgonc3xnoqu22csyqiom

Empowering NGOs in countering online hate messages

Yi-Ling Chung, Serra Sinem Tekiroğlu, Sara Tonelli, Marco Guerini
2021 Online Social Networks and Media  
Studies on online hate speech have mostly focused on the automated detection of harmful messages.  ...  Little attention has been devoted so far to the development of effective strategies to fight hate speech, in particular through the creation of counter-messages.  ...  on social media may limit the right to freedom of speech and diverse opinions.  ... 
doi:10.1016/j.osnem.2021.100150 fatcat:cz445fc6irhejdcyvh23akvr7q

Analyzing the Targets of Hate in Online Social Media [article]

Leandro Silva, Mainack Mondal, Denzil Correa, Fabricio Benevenuto, Ingmar Weber
2016 arXiv   pre-print
Despite its magnitude and scale, there is a significant gap in understanding the nature of hate speech on social media.  ...  In this paper, we provide the first of a kind systematic large scale measurement study of the main targets of hate speech in online social media.  ...  Our effort consists of characterizing hate speech in common social media, focusing on identifying the main targets of hateful messages.  ... 
arXiv:1603.07709v1 fatcat:mvtcrcyw2nc6nbfftk3rxaroia

LINGUISTIC ANALYSIS OF SLAVIC MEDIA TEXTS CONTAINING HATE SPEECH

Larysa Gorodnycha, Maryna Olkhovyk, Svitlana Gergul
2020 EUREKA Social and Humanities  
The authors define the causes of the hate speech usage in the media texts and study the hate speech as the source of the modern vocabulary.  ...  The research describes the features of an editor's work on the texts with the hate speech and methods of its neutralization, as well as proven discriminatory manifestation of hate speech in political neologisms  ...  Acknowledgments This article is the part of a research grant programme Erasmus+, Jean Monnet Project "European Antitotalitarian Practices") (№ 599704-EPP-1-2018-1-UA-EPPJMO-MODULE).  ... 
doi:10.21303/2504-5571.2020.001540 fatcat:mmnp7t5aazcvzgdimguimmn4g4

Online Shaming via Social Media using Machine Learning: A Survey

Dige Vaishnavi A
2021 International Journal for Research in Applied Science and Engineering Technology  
The major social networking sites have become a target platform for users to disperse a large amount of irrelevant and unwanted information.  ...  Twitter, it has become one of the most extravagant platforms of all time and, most popular micro blogging services which is generally used to share unreasonable amount of opinions.  ...  RELATED WORK A survey on hate speech detection. Given the steadily growing body of social media content, the amount of online hate speech is also increasing.  ... 
doi:10.22214/ijraset.2021.32964 fatcat:62cmgbhqhnbkzpqo77mo4udbqm

Antisemitism on Twitter: Collective Efficacy and the Role of Community Organisations in Challenging Online Hate Speech

Sefa Ozalp, Matthew L. Williams, Pete Burnap, Han Liu, Mohamed Mostafa
2020 Social Media + Society  
This study is the first to demonstrate that Sampson's classic sociological concept of collective efficacy can be observed on social media (SM).  ...  On SM, counter-speech posted by credible, capable and willing actors can be an effective measure to prevent harmful narratives.  ...  He has been involved in grants in worth in excess of £14 m, leading large awards from EPSRC, ESRC, and industry on the topics of social data science and cybersecurity analytics-the fusion of AI, cybersecurity  ... 
doi:10.1177/2056305120916850 fatcat:chpsm6gxp5e37fs27qdiwxm5wi

Public Prejudicial Discourse as a Global Socio-Ethnic Phenomenon: Using Digital Media to Limit Detrimental Language Flows

Emmanuel K. Ngwainmbi
2021 Communication, Society and Media  
Nevertheless, prejudice is a negative attitude and feeling toward an individual based solely on their membership in a particular social group (Allport, 1954); it is common against an unfamiliar cultural  ...  This paper analyzes some behavioral theories and uses the matrix of self-awareness and its ability to unlock our understanding of communication between groups and enhance group cultures.  ...  Communication, Society and Media Vol. 4, No. 3, 2021 Communication, Society and Media Vol. 4, No. 3, 2021  ... 
doi:10.22158/csm.v4n3p1 fatcat:ayh4mh323zfutnahrwrzdaedhm

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

Komal Florio, Valerio Basile, Marco Polignano, Pierpaolo Basile, Viviana Patti
2020 Applied Sciences  
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  ...  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.  ...  This is particularly relevant in the context of hate speech on social media, where users very often react to breaking news from media and relevant real-life events.  ... 
doi:10.3390/app10124180 fatcat:sd6ssuknl5hynl4kkpldyeo46a

Modeling Islamist Extremist Communications on Social Media using Contextual Dimensions: Religion, Ideology, and Hate [article]

Ugur Kursuncu, Manas Gaur, Carlos Castillo, Amanuel Alambo, K. Thirunarayan, Valerie Shalin, Dilshod Achilov, I. Budak Arpinar, Amit Sheth
2020 arXiv   pre-print
hate speech corpus for hate.  ...  The efforts to contain the ever-evolving extremism on social media platforms have remained inadequate and mostly ineffective.  ...  the presentation of this work.  ... 
arXiv:1908.06520v3 fatcat:zlzp2lvseffhxgpfuaknazk4dq

Challenges of Hate Speech Detection in Social Media

György Kovács, Pedro Alonso, Rajkumar Saini
2021 SN Computer Science  
AbstractThe detection of hate speech in social media is a crucial task.  ...  We have applied our model on the HASOC2019 corpus, and attained a macro F1 score of 0.63 in hate speech detection on the test set of HASOC.  ...  Challenges of Detecting Hateful and Offensive Speech There are many layers to the difficulty of automatically detecting hateful and/or offensive speech, particularly in social media.  ... 
doi:10.1007/s42979-021-00457-3 fatcat:hv3ktmpk55dvdjaflv3ad5x5iu

"Contro L'Odio": A Platform for Detecting, Monitoring and Visualizing Hate Speech against Immigrants in Italian Social Media

Arthur T. E. Capozzi, Mirko Lai, Valerio Basile, Fabio Poletto, Manuela Sanguinetti, Cristina Bosco, Viviana Patti, Giancarlo Ruffo, Cataldo Musto, Marco Polignano, Giovanni Semeraro, Marco Stranisci
2020 Italian Journal of Computational Linguistics  
It applies a combination of computational linguistics techniques for hate speech detection and data visualization tools on data drawn from Twitter.  ...  , and on the creation of positive narratives.  ...  Acknowledgments The work of all the authors was partially funded by Italian Ministry of Labor (Contro l'Odio: tecnologie informatiche, percorsi formativi e storytelling partecipativo per combattere l'intolleranza  ... 
doi:10.4000/ijcol.659 fatcat:slwwa5kmmnaydhpmkga6bf35gq

Cyber Bullying Detection on Social Media using Machine Learning

Aditya Desai, Shashank Kalaskar, Omkar Kumbhar, Rashmi Dhumal, M.D. Patil, V.A. Vyawahare
2021 ITM Web of Conferences  
Many of the traditional machine learning models have been implemented in the past for the automatic detection of cyberbullying on social media.  ...  Usage of internet and social media backgrounds tends in the use of sending, receiving and posting of negative, harmful, false or mean content about another individual which thus means Cyberbullying.  ...  The model is based on the prediction of hate speech tweets.  ... 
doi:10.1051/itmconf/20214003038 fatcat:5iql7i7l6vac7nloblg6cnmjau
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