92 citations · 211 across the 24 of their papers we have counts for
32 papers
Overview of AuTexTification at IberLEF 2023: Detection and Attribution of Machine-Generated Text in Multiple Domains
Areg Mikael Sarvazyan, José Ángel González, Marc Franco-Salvador +3
This paper presents the overview of the AuTexTification shared task as part of the IberLEF 2023 Workshop in Iberian Languages Evaluation Forum, within the framework of the SEPLN 20…
Mitigating Negative Transfer with Task Awareness for Sexism, Hate Speech, and Toxic Language Detection
Angel Felipe Magnossão de Paula, Paolo Rosso, Damiano Spina
This paper proposes a novelty approach to mitigate the negative transfer problem. In the field of machine learning, the common strategy is to apply the Single-Task Learning approac…
Transformers and Ensemble methods: A solution for Hate Speech Detection in Arabic languages
Angel Felipe Magnossão de Paula, Imene Bensalem, Paolo Rosso +1
This paper describes our participation in the shared task of hate speech detection, which is one of the subtasks of the CERIST NLP Challenge 2022. Our experiments evaluate the perf…
It's Just a Matter of Time: Detecting Depression with Time-Enriched Multimodal Transformers
Ana-Maria Bucur, Adrian Cosma, Paolo Rosso +1
Depression detection from user-generated content on the internet has been a long-lasting topic of interest in the research community, providing valuable screening tools for psychol…
Multilingual Detection of Check-Worthy Claims using World Languages and Adapter Fusion
Ipek Baris Schlicht, Lucie Flek, Paolo Rosso
Check-worthiness detection is the task of identifying claims, worthy to be investigated by fact-checkers. Resource scarcity for non-world languages and model learning costs remain…
Fake News and Hate Speech: Language in Common
Berta Chulvi, Alejandro Toselli, Paolo Rosso
In this paper we raise the research question of whether fake news and hate speech spreaders share common patterns in language. We compute a novel index, the ingroup vs outgroup ind…
Overview of the Shared Task on Fake News Detection in Urdu at FIRE 2020
Maaz Amjad, Grigori Sidorov, Alisa Zhila +2
This overview paper describes the first shared task on fake news detection in Urdu language. The task was posed as a binary classification task, in which the goal is to differentia…
An End-to-End Set Transformer for User-Level Classification of Depression and Gambling Disorder
Ana-Maria Bucur, Adrian Cosma, Liviu P. Dinu +1
This work proposes a transformer architecture for user-level classification of gambling addiction and depression that is trainable end-to-end. As opposed to other methods that oper…
Unsupervised Ranking and Aggregation of Label Descriptions for Zero-Shot Classifiers
Angelo Basile, Marc Franco-Salvador, Paolo Rosso
Zero-shot text classifiers based on label descriptions embed an input text and a set of labels into the same space: measures such as cosine similarity can then be used to select th…
Cryptocurrency Bubble Detection: A New Stock Market Dataset, Financial Task & Hyperbolic Models
Ramit Sawhney, Shivam Agarwal, Vivek Mittal +3
The rapid spread of information over social media influences quantitative trading and investments. The growing popularity of speculative trading of highly volatile assets such as c…
FACTOID: A New Dataset for Identifying Misinformation Spreaders and Political Bias
Flora Sakketou, Joan Plepi, Riccardo Cervero +3
Proactively identifying misinformation spreaders is an important step towards mitigating the impact of fake news on our society. In this paper, we introduce a new contemporary Redd…
Detecting early signs of depression in the conversational domain: The role of transfer learning in low-resource scenarios
Petr Lorenc, Ana-Sabina Uban, Paolo Rosso +1
The high prevalence of depression in society has given rise to the need for new digital tools to assist in its early detection. To this end, existing research has mainly focused on…
UPV at TREC Health Misinformation Track 2021 Ranking with SBERT and Quality Estimators
Ipek Baris Schlicht, Angel Felipe Magnossão de Paula, Paolo Rosso
Health misinformation on search engines is a significant problem that could negatively affect individuals or public health. To mitigate the problem, TREC organizes a health misinfo…
UPV at CheckThat! 2021: Mitigating Cultural Differences for Identifying Multilingual Check-worthy Claims
Ipek Baris Schlicht, Angel Felipe Magnossão de Paula, Paolo Rosso
Identifying check-worthy claims is often the first step of automated fact-checking systems. Tackling this task in a multilingual setting has been understudied. Encoding inputs with…
Studying Fake News Spreading, Polarisation Dynamics, and Manipulation by Bots: a Tale of Networks and Language
Giancarlo Ruffo, Alfonso Semeraro, Anastasia Giachanou +1
With the explosive growth of online social media, the ancient problem of information disorders interfering with news diffusion has surfaced with a renewed intensity threatening our…
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…
Analysis and tuning of hierarchical topic models based on Renyi entropy approach
Sergei Koltcov, Vera Ignatenko, Maxim Terpilovskii +1
Hierarchical topic modeling is a potentially powerful instrument for determining the topical structure of text collections that allows constructing a topical hierarchy representing…
Multilingual Irony Detection with Dependency Syntax and Neural Models
Alessandra Teresa Cignarella, Valerio Basile, Manuela Sanguinetti +3
This paper presents an in-depth investigation of the effectiveness of dependency-based syntactic features on the irony detection task in a multilingual perspective (English, Spanis…
Classifier Combination Approach for Question Classification for Bengali Question Answering System
Somnath Banerjee, Sudip Kumar Naskar, Paolo Rosso +1
Question classification (QC) is a prime constituent of automated question answering system. The work presented here demonstrates that the combination of multiple models achieve bet…
LIMSI_UPV at SemEval-2020 Task 9: Recurrent Convolutional Neural Network for Code-mixed Sentiment Analysis
Somnath Banerjee, Sahar Ghannay, Sophie Rosset +2
This paper describes the participation of LIMSI UPV team in SemEval-2020 Task 9: Sentiment Analysis for Code-Mixed Social Media Text. The proposed approach competed in SentiMix Hin…
#Brexit: Leave or Remain? The Role of User's Community and Diachronic Evolution on Stance Detection
Mirko Lai, Viviana Patti, Giancarlo Ruffo +1
Interest has grown around the classification of stance that users assume within online debates in recent years. Stance has been usually addressed by considering users posts in isol…
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…