Papers by Mourad Oussalah

3 papers
Data Expansion Using WordNet-based Semantic Expansion and Word Disambiguation for Cyberbullying Detection (2022.lrec-1)

Copied to clipboard

Challenge: Existing methods to identify cyberbullying from text are limited due to the complexity of the content and the lack of labeled large-scale corpus.
Approach: They propose a data augmentation-based approach that could enhance the automatic detection of cyberbullying in social media texts.
Outcome: The proposed approach overcomes limitations of social media posts with word sense disambiguation and synonymy relation . results show that the proposed approach improves on the existing classifiers with and without data augmentation.
Finnish Hate-Speech Detection on Social Media Using CNN and FinBERT (2022.lrec-1)

Copied to clipboard

Challenge: Existing tools to identify hate posts from social media are limited in the field of online hate speech detection.
Approach: They propose to use finBERT to generate a Finnish hate speech dataset . finBERt has a 91.7% accuracy and 90.8% F1 score value, they say .
Outcome: The proposed model outperforms state-of-the-art models in Finnish and other languages.
Causal Evidence Extraction and Triangulation in Crisis Reports using Large Language Models: A ReliefWeb-based Study (2026.findings-acl)

Copied to clipboard

Challenge: Humanitarian crises generate large volumes of narrative situation reports describing interventions and evolving outcomes.
Approach: They propose a large language model pipeline that extracts structured intervention-outcome records with direction and strength attributes.
Outcome: The proposed pipeline extracts structured intervention-outcome records with direction and strength attributes.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations