Julien Boyadjian


2015

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Etude de l’image de marque d’entités dans le cadre d’une plateforme de veille sur le Web social
Leila Khouas | Caroline Brun | Anne Peradotto | Jean-Valère Cossu | Julien Boyadjian | Julien Velcin
Actes de la 22e conférence sur le Traitement Automatique des Langues Naturelles. Démonstrations

Ce travail concerne l’intégration à une plateforme de veille sur internet d’outils permettant l’analyse des opinions émises par les internautes à propos d’une entité, ainsi que la manière dont elles évoluent dans le temps. Les entités considérées peuvent être des personnes, des entreprises, des marques, etc. Les outils implémentés sont le produit d’une collaboration impliquant plusieurs partenaires industriels et académiques dans le cadre du projet ANR ImagiWeb.

2014

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Investigating the Image of Entities in Social Media: Dataset Design and First Results
Julien Velcin | Young-Min Kim | Caroline Brun | Jean-Yves Dormagen | Eric SanJuan | Leila Khouas | Anne Peradotto | Stephane Bonnevay | Claude Roux | Julien Boyadjian | Alejandro Molina | Marie Neihouser
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

The objective of this paper is to describe the design of a dataset that deals with the image (i.e., representation, web reputation) of various entities populating the Internet: politicians, celebrities, companies, brands etc. Our main contribution is to build and provide an original annotated French dataset. This dataset consists of 11527 manually annotated tweets expressing the opinion on specific facets (e.g., ethic, communication, economic project) describing two French policitians over time. We believe that other researchers might benefit from this experience, since designing and implementing such a dataset has proven quite an interesting challenge. This design comprises different processes such as data selection, formal definition and instantiation of an image. We have set up a full open-source annotation platform. In addition to the dataset design, we present the first results that we obtained by applying clustering methods to the annotated dataset in order to extract the entity images.