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


Abstract
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.
Anthology ID:
L14-1272
Volume:
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)
Month:
May
Year:
2014
Address:
Reykjavik, Iceland
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
818–822
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/302_Paper.pdf
DOI:
Bib Export formats:
BibTeX MODS XML EndNote
PDF:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/302_Paper.pdf