Offensive Language Identification
Related Papers
CN-HIT-MI.T at SemEval-2019 Task 6: Offensive Language Identification Based on BiLSTM with Double Attention
AbstractOffensive language has become pervasive in social media. In Offensive Language Identification tasks, it may be difficult to predict accurately only according to the surface words. So we try to …...
Emad at SemEval-2019 Task 6: Offensive Language Identification using Traditional Machine Learning and Deep Learning approaches
AbstractIn this paper, the used methods and the results obtained by our team, entitled Emad, on the OffensEval 2019 shared task organized at SemEval 2019 are presented. The OffensEval shared …...
Embeddia at SemEval-2019 Task 6: Detecting Hate with Neural Network and Transfer Learning Approaches
AbstractSemEval 2019 Task 6 was OffensEval: Identifying and Categorizing Offensive Language in Social Media. The task was further divided into three sub-tasks: offensive language identification, automatic categorization of offense types, …...
JU_ETCE_17_21 at SemEval-2019 Task 6: Efficient Machine Learning and Neural Network Approaches for Identifying and Categorizing Offensive Language in Tweets
AbstractThis paper describes our system submissions as part of our participation (team name: JU_ETCE_17_21) in the SemEval 2019 shared task 6: “OffensEval: Identifying and Catego- rizing Offensive Language in Social …...
NULI at SemEval-2019 Task 6: Transfer Learning for Offensive Language Detection using Bidirectional Transformers
AbstractTransfer learning and domain adaptive learning have been applied to various fields including computer vision (e.g., image recognition) and natural language processing (e.g., text classification). One of the benefits of …...
SSN_NLP at SemEval-2019 Task 6: Offensive Language Identification in Social Media using Traditional and Deep Machine Learning Approaches
AbstractOffensive language identification (OLI) in user generated text is automatic detection of any profanity, insult, obscenity, racism or vulgarity that degrades an individual or a group. It is helpful for …...
ALT at SemEval-2020 Task 12: Arabic and English Offensive Language Identification in Social Media
AbstractThis paper describes the systems submitted by the Arabic Language Technology group (ALT) at SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media. We focus on sub-task A (Offensive …...
Galileo at SemEval-2020 Task 12: Multi-lingual Learning for Offensive Language Identification Using Pre-trained Language Models
AbstractThis paper describes Galileo’s performance in SemEval-2020 Task 12 on detecting and categorizing offensive language in social media. For Offensive Language Identification, we proposed a multi-lingual method using Pre-trained Language …...
Garain at SemEval-2020 Task 12: Sequence Based Deep Learning for Categorizing Offensive Language in Social Media
AbstractSemEval-2020 Task 12 was OffenseEval: Multilingual Offensive Language Identification inSocial Media (Zampieri et al., 2020). The task was subdivided into multiple languages anddatasets were provided for each one. The task …...
Hitachi at SemEval-2020 Task 12: Offensive Language Identification with Noisy Labels Using Statistical Sampling and Post-Processing
AbstractIn this paper, we present our participation in SemEval-2020 Task-12 Subtask-A (English Language) which focuses on offensive language identification from noisy labels. To this end, we developed a hybrid system …...
IR3218-UI at SemEval-2020 Task 12: Emoji Effects on Offensive Language IdentifiCation
AbstractIn this paper, we present our approach and the results of our participation in OffensEval 2020. There are three sub-tasks in OffensEval 2020 namely offensive language identification (sub-task A), automatic …...
KS@LTH at SemEval-2020 Task 12: Fine-tuning Multi- and Monolingual Transformer Models for Offensive Language Detection
AbstractThis paper describes the KS@LTH system for SemEval-2020 Task 12 OffensEval2: Multilingual Offensive Language Identification in Social Media. We compare mono- and multilingual models based on fine-tuning pre-trained transformer models …...
LT@Helsinki at SemEval-2020 Task 12: Multilingual or Language-specific BERT?
AbstractThis paper presents the different models submitted by the LT@Helsinki team for the SemEval 2020 Shared Task 12. Our team participated in sub-tasks A and C; titled offensive language identification …...
NLPDove at SemEval-2020 Task 12: Improving Offensive Language Detection with Cross-lingual Transfer
AbstractThis paper describes our approach to the task of identifying offensive languages in a multilingual setting. We investigate two data augmentation strategies: using additional semi-supervised labels with different thresholds and …...
nlpUP at SemEval-2020 Task 12 : A Blazing Fast System for Offensive Language Detection
AbstractIn this paper, we introduce our submission for the SemEval Task 12, sub-tasks A and B for offensive language identification and categorization in English tweets. This year the data set …...
Ssn_nlp at SemEval 2020 Task 12: Offense Target Identification in Social Media Using Traditional and Deep Machine Learning Approaches
AbstractOffensive language identification (OLI) in user generated text is automatic detection of any profanity, insult, obscenity, racism or vulgarity that is addressed towards an individual or a group. Due to …...
SSN_NLP_MLRG at SemEval-2020 Task 12: Offensive Language Identification in English, Danish, Greek Using BERT and Machine Learning Approach
AbstractOffensive language identification is to detect the hurtful tweets, derogatory comments, swear words on social media. As an emerging growth of social media communication, offensive language detection has received more …...
TECHSSN at SemEval-2020 Task 12: Offensive Language Detection Using BERT Embeddings
AbstractThis paper describes the work of identifying the presence of offensive language in social media posts and categorizing a post as targeted to a particular person or not. The work …...
XD at SemEval-2020 Task 12: Ensemble Approach to Offensive Language Identification in Social Media Using Transformer Encoders
AbstractThis paper presents six document classification models using the latest transformer encoders and a high-performing ensemble model for a task of offensive language identification in social media. For the individual …...
An Exploratory Analysis of the Relation between Offensive Language and Mental Health
In this paper, we analyze the interplay be- tween the use of offensive language and men- tal health. We acquired publicly available datasets created for offensive language identi- fication and …...
Cross-lingual Offensive Language Identification for Low Resource Languages: The Case of Marathi
AbstractThe widespread presence of offensive language on social media motivated the development of systems capable of recognizing such content automatically. Apart from a few notable exceptions, most research on automatic …...