References of "Benamara, Farah"
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See detailA three-level classification of French tweets in ecological crises
Kozlowski, Diego UL; Lannelongue, Elisa; Saudemont, Frédéric et al

in Information Processing and Management (2020), 57(5),

The possibilities that emerge from micro-blogging generated content for crisis-related situations make automatic crisis management using natural language processing techniques a hot research topic. Our ... [more ▼]

The possibilities that emerge from micro-blogging generated content for crisis-related situations make automatic crisis management using natural language processing techniques a hot research topic. Our aim here is to contribute to this line of research focusing for the first time on French tweets related to ecological crises in order to support the French Civil Security and Crisis Management Department to provide immediate feedback on the expectations of the populations involved in the crisis. We propose a new dataset manually annotated according to three dimensions: relatedness, urgency and intentions to act. We then experiment with binary classification (useful vs. non useful), three-class (non useful vs. urgent vs. non urgent) and multiclass classification (i.e., intention to act categories) relying on traditional feature-based machine learning using both state of the art and new features. We also explore several deep learning models trained with pre-trained word embeddings as well as contextual embeddings. We then investigate three transfer learning strategies to adapt these models to the crisis domain. We finally experiment with multi-input architectures by incorporating different metadata extra-features to the network. Our deep models, evaluated in random sampling, out-of-event and out-of-type configurations, show very good performances outperforming several competitive baselines. Our results define the first contribution to the field of crisis management in French social media. [less ▲]

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See detailIndividual Opinions-Based Judgment Aggregation Procedures
Benamara, Farah; Kaci, Souhila; Pigozzi, Gabriella UL

in Modeling Decisions for Artificial Intelligence (2010)

Judgment aggregation is a recent formal discipline that studies how to aggregate individual judgments on logically connected propositions to form collective decisions on the same propositions. Despite the ... [more ▼]

Judgment aggregation is a recent formal discipline that studies how to aggregate individual judgments on logically connected propositions to form collective decisions on the same propositions. Despite the apparent simplicity of the problem, the aggregation of individual judgments can result in an inconsistent outcome. This seriously troubles this research field. Expert panels, legal courts, boards, and councils are only some examples of group decision situations that confront themselves with such aggregation problems. So far, the existing framework and procedures considered in the literature are idealized. Our goal is to enrich standard judgment aggregation by allowing the individuals to agree or disagree on the decision rule. Moreover, the group members have the possibility to abstain or express neutral judgments. This provides a more realistic framework and, at the same time, consents the definition of an aggregation procedure that escapes the inconsistent group outcome. [less ▲]

Detailed reference viewed: 79 (0 UL)