Abstract

We present a semi-automatic tool that assists experts in their daily work of monitoring the reputation of entities—companies, organizations or public figures—in Twitter. The tool automatically annotates tweets for relevance (Is the tweet about the entity?), reputational polarity (Does the tweet convey positive or negative implications for the reputation of the entity?), groups tweets in topics and display topics in decreasing order of relevance from a reputational perspective. The interface helps the user to understand the content being analyzed and also to produce a manually annotated version of the data starting from the output of the automatic annotation processes.

Demo Access

The demo titled ORMA: A Semi-Automatic Tool for Online Reputation Monitoring in Twitter has been presented at ECIR'14. Recently, ORMA has been shown at COMMIT's 'The Big Future of Data' Event with a new, fresh look & feel. The new version of ORMA can be accessed through the following link:

http://mercurio.lsi.uned.es:8080/orma2014COMMIT

The demo requires login information. Please contact Jorge Carrillo-de-Albornoz or Damiano Spina to receive this information.


Citation

Please cite the article below if you use this resource in your research: 
J. Carrillo-de-Albornoz, E. Amigó, D. Spina, J. Gonzalo.
ORMA: A Semi-Automatic Tool for Online Reputation Monitoring in Twitter
Proceedings of the 36th European Conference on Information Retrieval (ECIR). 2014.

BibTex

@inproceedings{jcalbornoz2014orma,
  author = {Carrillo-de-Albornoz, J. and Amig{\'o}, E. and Spina, D. and Gonzalo, J.},
  booktitle = {{Proceedings of the 36th European Conference on Information Retrieval (ECIR)}},
  title = {{ORMA: A Semi-Automatic Tool for Online Reputation Monitoring in Twitter}},
  year = {2014}}
}