Large-scale news entity sentiment analysis

no code implementations • RANLP 2017 • Ralf Steinberger, Stefanie Hegele, Hristo Tanev, Leonida della Rocca

We work on detecting positive or negative sentiment towards named entities in very large volumes of news articles.

Bias Detection Negation +2

Media monitoring and information extraction for the highly inflected agglutinative language Hungarian

no code implementations • LREC 2014 • J{\'u}lia Pajzs, Ralf Steinberger, Maud Ehrmann, Mohamed Ebrahim, Leonida della Rocca, Stefano Bucci, Eszter Simon, Tam{\'a}s V{\'a}radi

In this paper, we describe the effort of adding to EMM Hungarian text mining tools for news gathering; document categorisation; named entity recognition and classification for persons, organisations and locations; name lemmatisation; quotation recognition; and cross-lingual linking of related news clusters.

Information Retrieval named-entity-recognition +2

Acronym recognition and processing in 22 languages

no code implementations • RANLP 2013 • Maud Ehrmann, Leonida della Rocca, Ralf Steinberger, Hristo Tanev

We are presenting work on recognising acronyms of the form Long-Form (Short-Form) such as "International Monetary Fund (IMF)" in millions of news articles in twenty-two languages, as part of our more general effort to recognise entities and their variants in news text and to use them for the automatic analysis of the news, including the linking of related news across languages.