13 citations · 29 across the 7 of their papers we have counts for
10 papers
Better Handling Coreference Resolution in Aspect Level Sentiment Classification by Fine-Tuning Language Models
Dhruv Mullick, Bilal Ghanem, Alona Fyshe
Customer feedback is invaluable to companies as they refine their products. Monitoring customer feedback can be automated with Aspect Level Sentiment Classification (ALSC) which al…
DISTO: Evaluating Textual Distractors for Multi-Choice Questions using Negative Sampling based Approach
Bilal Ghanem, Alona Fyshe
Multiple choice questions (MCQs) are an efficient and common way to assess reading comprehension (RC). Every MCQ needs a set of distractor answers that are incorrect, but plausible…
Discriminative Models Can Still Outperform Generative Models in Aspect Based Sentiment Analysis
Dhruv Mullick, Alona Fyshe, Bilal Ghanem
Aspect-based Sentiment Analysis (ABSA) helps to explain customers' opinions towards products and services. In the past, ABSA models were discriminative, but more recently generativ…
Question Generation for Reading Comprehension Assessment by Modeling How and What to Ask
Bilal Ghanem, Lauren Lutz Coleman, Julia Rivard Dexter +2
Reading is integral to everyday life, and yet learning to read is a struggle for many young learners. During lessons, teachers can use comprehension questions to increase engagemen…
Let-Mi: An Arabic Levantine Twitter Dataset for Misogynistic Language
Hala Mulki, Bilal Ghanem
Online misogyny has become an increasing worry for Arab women who experience gender-based online abuse on a daily basis. Misogyny automatic detection systems can assist in the proh…
FakeFlow: Fake News Detection by Modeling the Flow of Affective Information
Bilal Ghanem, Simone Paolo Ponzetto, Paolo Rosso +1
Fake news articles often stir the readers' attention by means of emotional appeals that arouse their feelings. Unlike in short news texts, authors of longer articles can exploit su…
Irony Detection in a Multilingual Context
Bilal Ghanem, Jihen Karoui, Farah Benamara +2
This paper proposes the first multilingual (French, English and Arabic) and multicultural (Indo-European languages vs. less culturally close languages) irony detection system. We e…
FacTweet: Profiling Fake News Twitter Accounts
Bilal Ghanem, Simone Paolo Ponzetto, Paolo Rosso
We present an approach to detect fake news in Twitter at the account level using a neural recurrent model and a variety of different semantic and stylistic features. Our method ext…
TexTrolls: Identifying Russian Trolls on Twitter from a Textual Perspective
Bilal Ghanem, Davide Buscaldi, Paolo Rosso
The online new emerging suspicious users, that usually are called trolls, are one of the main sources of hate, fake, and deceptive online messages. Some agendas are utilizing these…
An Emotional Analysis of False Information in Social Media and News Articles
Bilal Ghanem, Paolo Rosso, Francisco Rangel
Fake news is risky since it has been created to manipulate the readers' opinions and beliefs. In this work, we compared the language of false news to the real one of real news from…