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A Dictionary-based Approach to Racism Detection in Dutch Social Media [article]

Stéphan Tulkens, Lisa Hilte, Elise Lodewyckx, Ben Verhoeven, Walter Daelemans
2016 arXiv   pre-print
We present a dictionary-based approach to racism detection in Dutch social media comments, which were retrieved from two public Belgian social media sites likely to attract racist reactions.  ...  A second dictionary was created through automatic expansion using a word2vec model trained on a large corpus of general Dutch text.  ...  In this study, we try to automatically detect racist language in Dutch social media comments, using a dictionary-based approach.  ... 
arXiv:1608.08738v1 fatcat:5rpxqv2jtjdyjnevqfwernoiba

A Classification Model Based on Machine Learning for Detecting Racist Comments on Social Media Platforms

D. Allenotor, Department of Computer Science Federal University of Petroleum Resources Effurun (FUPRE) Effurun, Delta State, Nigeria E-mails: allenotor.david@fupre.edu.ng, D. A. Oyemade, oyemade.david@fupre.edu.ng
2021 Advances in Multidisciplinary & Scientific Research Journal Publication  
English football clubs have also threatened a boycott of social media in a bid to eradicate online hate.  ...  We will be building a classification model using machine learning to detect racist comments on social media platforms.  ...  In their report, they presented a dictionary-based approach to racism detection in Dutch social media comments.  ... 
doi:10.22624/aims/bhi/v7n1p9 fatcat:a65hildfrbhmfdocxeg6qem6jq

Multilingual Cross-domain Perspectives on Online Hate Speech [article]

Tom De Smedt, Sylvia Jaki, Eduan Kotzé, Leïla Saoud, Maja Gwóźdź, Guy De Pauw, Walter Daelemans
2018 arXiv   pre-print
In this report, we present a study of eight corpora of online hate speech, by demonstrating the NLP techniques that we used to collect and analyze the jihadist, extremist, racist, and sexist content.  ...  Analysis of the multilingual corpora shows that the different contexts share certain characteristics in their hateful rhetoric.  ...  of racism on social media (Benveniste & Pingaud, 2016) .  ... 
arXiv:1809.03944v1 fatcat:bkk65x2xivejdfl3ihf34yfwtu

Automatic detection of cyberbullying in social media text

Cynthia Van Hee, Gilles Jacobs, Chris Emmery, Bart Desmet, Els Lefever, Ben Verhoeven, Guy De Pauw, Walter Daelemans, Véronique Hoste, Hussein Suleman
2018 PLoS ONE  
The focus of this paper is on automatic cyberbullying detection in social media text by modelling posts written by bullies, victims, and bystanders of online bullying.  ...  While social media offer great communication opportunities, they also increase the vulnerability of young people to threatening situations online.  ...  Our experiments reveal that the current approach is a promising strategy for detecting signals of cyberbullying Automatic detection of cyberbullying in social media text on social media automatically.  ... 
doi:10.1371/journal.pone.0203794 fatcat:jtre4sgvxvcrximuac4vbznzti

Demographic Word Embeddings for Racism Detection on Twitter

Mohammed Hasanuzzaman, Gaël Dias, Andy Way
2017 International Joint Conference on Natural Language Processing  
In this study, we present a supervised learning strategy to detect racist language on Twitter based on word embedding that incorporate demographic (Age, Gender, and Location) information.  ...  Most social media platforms grant users freedom of speech by allowing them to freely express their thoughts, beliefs, and opinions.  ...  Tulkens et al. (2016) present a dictionary-based approach to racism detection in Dutch social media comments following the findings of Burnap and Williams (2016) .  ... 
dblp:conf/ijcnlp/HasanuzzamanDW17 fatcat:khjfopdybjblhokhumfl2g4q2i

Automatic Hate Speech Detection using Machine Learning: A Comparative Study

Sindhu Abro, Sarang Shaikh, Zahid Hussain, Zafar Ali, Sajid Khan, Ghulam Mujtaba
2020 International Journal of Advanced Computer Science and Applications  
Thus, to solve this emerging issue in social media sites, recent studies employed a variety of feature engineering techniques and machine learning algorithms to automatically detect the hate speech messages  ...  The increasing use of social media and information sharing has given major benefits to humanity.  ...  [22] also used a dictionarybased approach for the automatic detection of racism in Dutch Social Media.  ... 
doi:10.14569/ijacsa.2020.0110861 fatcat:b2ruvjdqujb4xlnwa4hzb3izgu

Aggression Detection in Social Media using Deep Neural Networks

Sreekanth Madisetty, Maunendra Sankar Desarkar
2018 International Conference on Computational Linguistics  
A majority voting based ensemble method is used to combine these classifiers (CNN, LSTM, and Bi-LSTM).  ...  In this paper, we work on the problem of aggression detection in social media. Aggression can sometimes be expressed directly or overtly or it can be hidden or covert in the text.  ...  A dictionary-based approach to detect racism in Dutch social media is proposed in (Tulkens et al., 2016) . The authors have used three dictionaries.  ... 
dblp:conf/coling/MadisettyD18 fatcat:erxcvr2swjaqffzbk7kghfauqu

SOCIAL NETWORK HATE SPEECH DETECTION FOR AMHARIC LANGUAGE

Zewdie Mossie, Jenq-Haur Wang
2018 Figshare  
With this everincreasing volume of social media data, hate speech identification becomes a challenge in aggravating conflict between citizens of nations.  ...  The anonymity of social networks makes it attractive for hate speech to mask their criminal activities online posing a challenge to the world and in particular Ethiopia.  ...  Existing Techniques Used in Hate Speech Detection in Social Media The study of hate speech detection has been growing only in the few last years.  ... 
doi:10.6084/m9.figshare.6714884.v1 fatcat:yifu4maxsvbd3m4t2zmh2eafzq

A Comparison of Classification Models to Detect Cyberbullying in the Peruvian Spanish Language on Twitter

Ximena M. Cuzcano, Victor H.
2020 International Journal of Advanced Computer Science and Applications  
through social media.  ...  Cyberbullying is a social problem in which bullies' actions are more harmful than in traditional forms of bullying as they have the power to repeatedly humiliate the victim in front of an entire community  ...  The next section presents the related works aiming to automatically detect cyberbullying in social media.  ... 
doi:10.14569/ijacsa.2020.0111018 fatcat:cfsjfsp4nfdd7bpz4r3cr6iram

Tackling Online Abuse: A Survey of Automated Abuse Detection Methods [article]

Pushkar Mishra, Helen Yannakoudakis, Ekaterina Shutova
2020 arXiv   pre-print
We describe the existing datasets and review the computational approaches to abuse detection, analyzing their strengths and limitations.  ...  In this paper, we present a comprehensive survey of the methods that have been proposed to date, thus providing a platform for further development of this area.  ...  Introduction With the advent of social media, anti-social and abusive behavior has become a prominent occurrence online.  ... 
arXiv:1908.06024v2 fatcat:53nwpcbspjdbrnyplzmsyjxmpu

What Truly Matters? Using Linguistic Cues for Analyzing the #BlackLivesMatter Movement and its Counter Protests: 2013 to 2020 [article]

Jamell Dacon, Jiliang Tang
2021 arXiv   pre-print
We conduct a multi-level text analysis on 36,984,559 tweets to investigate users' behaviors to examine the language used and understand the impact of digital activism on social media within each social  ...  In this work, we administer an innovative study of digital activism by exploiting social media as an authoritative tool to examine and analyze the linguistic cues and thematic relationships in these three  ...  Due to the nature of the dataset, we apply a deductive approach s.t. we assume common themes and/or topics that each 100K dataset should reflect based on prior knowledge and keyword usage as seen in Figure  ... 
arXiv:2109.12192v1 fatcat:jusrohubz5ewnmymn5ppsywnwy

Applied Linguistics to Identify and Contrast Racist 'Hate Speech': Cases from the English and Italian Language

Gabriella B. Klein
2018 Applied Linguistics Research Journal  
Acknowledgements The present paper is based on research findings from a project co-funded from 2014-2016 by the European Union: RADAR (Regulating AntiDiscrimination and AntiRacism, JUST/2013/FRAC/ AG/6271  ...  Hassan Soleimani from the Payame Noor University (Iran) for their kind invitation as plenary speaker to the 5 th International Conference on Applied Linguistics Issues in Istanbul, Turkey, October, 2018  ...  in society demands a multidisciplinary approach to research" (p. 50).  ... 
doi:10.14744/alrj.2018.36855 fatcat:4bxrgb23ejb4zbrygceoww2hzy

Detection of Racist Language in French Tweets

Natalia Vanetik, Elisheva Mimoun
2022 Information  
Therefore, the automated detection of offensive language and racism is in high demand, and it is a serious challenge.  ...  Toxic online content has become a major issue in recent years due to the exponential increase in the use of the internet.  ...  A multi-feature-based approach combining various lexicons and semantic-based features is presented by Almatarneh in [13] .  ... 
doi:10.3390/info13070318 fatcat:c35tk5r4gzfkthh6evmii6jzz4

Psychosocial Features for Hate Speech Detection in Code-switched Texts

Edward Ombui, School of Science and Technology, Africa Nazarene University, Nairobi, Kenya, Lawrence Muchemi, Peter Wagacha
2021 International Journal of Information Technology and Computer Science  
This study examines the problem of hate speech identification in codeswitched text from social media using a natural language processing approach.  ...  The study espouses a novel approach to handle this challenge by introducing a hierarchical approach that employs Latent Dirichlet Analysis to generate topic models that help build a high-level Psychosocial  ...  Daelemans, “The Automated Detection of Racist Discourse in Dutch Social Media,” CoRR, abs/1608.08738, 2016. [27] T. Davidson, D. Warmsley, M. Macy, and I.  ... 
doi:10.5815/ijitcs.2021.06.03 fatcat:zfpl6tc3ardzxambqazyqo2z3i

NLP@UIOWA at SemEval-2019 Task 6: Classifying the Crass using Multi-windowed CNNs

Jonathan Rusert, Padmini Srinivasan
2019 Proceedings of the 13th International Workshop on Semantic Evaluation  
Our system is a text based CNN, which learns only from the provided training data.  ...  This paper proposes a system for OffensEval (SemEval 2019 Task 6), which calls for a system to classify offensive language into several categories.  ...  Future work would aim to improve the current CNN design by testing different word windows and training techniques.  ... 
doi:10.18653/v1/s19-2125 dblp:conf/semeval/RusertS19 fatcat:72ha6cetbvgs3cnhvb7d2bai2m
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