[PDF] Top 20 The Effects of User Features on Twitter Hate Speech Detection
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The Effects of User Features on Twitter Hate Speech Detection
... a user who appears to sincerely wish to be part of a group, including professing, or conveying pseudo-sincere intentions, but whose real intentions are to cause disruption or to trigger conflict for the purposes ... See full document
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Are You a Racist or Am I Seeing Things? Annotator Influence on Hate Speech Detection on Twitter
... tors can produce relatively good annotations as com- pared to expert annotators. This can allow for a sig- nificant decrease in the annotations burden of expert annotators by asking them to primarily consider the cases ... See full document
5
ARHNet Leveraging Community Interaction for Detection of Religious Hate Speech in Arabic
... religious hate speech in the Arabic Twittersphere and build upon existing work in the linguistic aspects of social media (Shah et ...for Hate and Non-Hate, we first comprehensively replicated ... See full document
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SemEval 2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter
... the detection of hate speech against immigrants and women in Spanish and English messages extracted from ...of hate speech, and a finer-grained one devoted to identifying fur- ther ... See full document
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MineriaUNAM at SemEval 2019 Task 5: Detecting Hate Speech in Twitter using Multiple Features in a Combinatorial Framework
... detecting hate speech against immigrants and women in ...(A) detection of hate speech and (B) classification of hateful tweets as aggressive or not, and identification of the target ... See full document
6
An Italian Twitter Corpus of Hate Speech against Immigrants
... all hate speech is the same and that there are indeed different shades of intensity, our results show that much work is still to be done before these shades can be effectively defined and ...semantic ... See full document
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JCTDHS at SemEval 2019 Task 5: Detection of Hate Speech in Tweets using Deep Learning Methods, Character N gram Features, and Preprocessing Methods
... Analysis of the results presented in Table 1 shows that our best Macro F-measure score (as opposed to F1 of hate speech alone) for the test set (0.5) was obtained by a bidirectional RNN with 4 hidden ... See full document
5
A Dataset of Hindi English Code Mixed Social Media Text for Hate Speech Detection
... of hate speech. We retrieved 1,12,718 tweets from Twitter in json format, which consists of informa- tion such as timestamp, URL, text, user, re-tweets, replies, full name, id and ... See full document
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CIC at SemEval 2019 Task 5: Simple Yet Very Efficient Approach to Hate Speech Detection, Aggressive Behavior Detection, and Target Classification in Twitter
... (1) Hate Speech Detection against immigrants and women; (2) aggressive behavior and target on the Twitter ...as features for classifiers like MultinomialNB, Majority Voting, Logistic ... See full document
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ltl uni due at SemEval 2019 Task 5: Simple but Effective Lexico Semantic Features for Detecting Hate Speech in Twitter
... We present ltl.uni-due our submission to SemEval 2019 Task 5 Multilingual Detection of Hate. For building our system, We systematically compare a wide range of approaches – including neural net- work ... See full document
6
The Risk of Racial Bias in Hate Speech Detection
... of hate speech and abusive lan- guage on social media (Schmidt and Wiegand, ...published Twitter corpora include Golbeck et ...network features, rather than ... See full document
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LT3 at SemEval 2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter (hatEval)
... We applied the Twitter-specific tweetokenize (Sut- tles, 2013) 1 module for tokenization and prepro- cessing. With this module, we were able to en- sure all unicode emojis would be preserved. It also allowed us to ... See full document
5
The generalization performance of hate speech detection using machine learning
... in user-generated content on the ...of hate speech [2]. Hate speech is defined as speech that attacks a person or a group based on attributes such as race, religion, ethnic ... See full document
6
STUFIIT at SemEval 2019 Task 5: Multilingual Hate Speech Detection on Twitter with MUSE and ELMo Embeddings
... The input layer is fed into a convolutional layer. This layer performs a 1d convolution with 100 fil- ters and a kernel size of 4 with a relu activation function. This is then max pooled with a pool size of 4 and stride ... See full document
5
Know Center at SemEval 2019 Task 5: Multilingual Hate Speech Detection on Twitter using CNNs
... raw Twitter messages, several steps of pre-processing are ...tags. User mentions are replaced by "<user>" , numbers by "<number>" , web links by "<url>" and ... See full document
5
Leveraging Intra User and Inter User Representation Learning for Automated Hate Speech Detection
... Hate speech detection is a critical, yet chal- lenging problem in Natural Language Process- ing ...NLP hate speech detection approaches, the accu- racy is still ...existing ... See full document
6
Multi label Hate Speech and Abusive Language Detection in Indonesian Twitter
... and hate speech identification including identify the target, cate- gories, and level of hate ...ding features to basic features such as word n- grams is shown to improve classification ... See full document
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HATEMINER at SemEval 2019 Task 5: Hate speech detection against Immigrants and Women in Twitter using a Multinomial Naive Bayes Classifier
... mitigate hate speech. Although twitter condemns hate speech through its hateful conduct policy 1 , enforcing it is ...as hate speech and hence it is important to ... See full document
5
Hateful Symbols or Hateful People? Predictive Features for Hate Speech Detection on Twitter
... much of this moderation requires manual review of questionable documents, which not only limits how much a human annotator can be reviewed, but also introduces subjective notions of what consti- tutes hate ... See full document
6
GSI UPM at SemEval 2019 Task 5: Semantic Similarity and Word Embeddings for Multilingual Detection of Hate Speech Against Immigrants and Women on Twitter
... were features that helped in a meaningful manner, confirming the is- sues raised in ...proposed features was incre- ...the hate speech domain, it could be argued that attending to word context ... See full document
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