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Detecting Nastiness in Social Media
TLDR
This paper presents the initial NLP approach to detect invective posts as a first step to eventually detect and deter cyberbullying, and shows that this model not only works for the data set, but also can be successfully applied to different data sets.
ParsiNLU: A Suite of Language Understanding Challenges for Persian
TLDR
This work introduces ParsiNLU, the first benchmark in Persian language that includes a range of language understanding tasks—reading comprehension, textual entailment, and so on, and presents the first results on state-of-the-art monolingual and multilingual pre-trained language models on this benchmark and compares them with human performance.
RiTUAL-UH at TRAC 2018 Shared Task: Aggression Identification
TLDR
This paper presents the system for “TRAC 2018 Shared Task on Aggression Identification”, which uses a combination of lexical and semantic features for the English dataset but for Hindi data using only lexical features gave the best results.
Rating for Parents: Predicting Children Suitability Rating for Movies Based on Language of the Movies
TLDR
This paper proposes an RNN based architecture with attention that jointly models the genre and the emotions in the script to predict the MPAA rating and achieves 78% weighted F1-score for the classification model that outperforms the traditional machine learning method by 6%.
Aggression and Misogyny Detection using BERT: A Multi-Task Approach
TLDR
An end-to-end neural model using attention on top of BERT that incorporates a multi-task learning paradigm to address both the sub-tasks simultaneously is proposed.
Attending the Emotions to Detect Online Abusive Language
TLDR
A new corpus for the task of abusive language detection is presented that is collected from a semi-anonymous online platform, and unlike the majority of other available resources, is not created based on a specific list of bad words.
Age Suitability Rating: Predicting the MPAA Rating Based on Movie Dialogues
TLDR
This paper creates a corpus for movie MPAA ratings and proposes an RNN based architecture with attention that jointly models the genre and the emotions in the script to predict the MPAA rating.
Detecting Early Signs of Cyberbullying in Social Media
TLDR
This paper proposes a new approach to create a corpus suited for cyberbullying detection and investigates the possibility of designing a framework to monitor the streams of users’ online messages and detects the signs of cyberbullies as early as possible.