The Text and Data Mining Unit of the European Commission’s Joint Research 
Centre (JRC) is looking to fill one traineeship position in the field of:

Entity and Sentential-level Sentiment Analysis in the News

If you are interested, please follow the instructions provided at (Code: 
2018-IPR-I-000-9856 - ISPRA).

Deadline: 26/04/2017
Job description:         
Traineeship rules:      
Starting date:                    As soon as possible
Duration:                          5 months
Allowance:                         Up to approximately 1000 Euro per month.
The JRC-
Text and Data Mining Unit :
JRC-EMM products:   
JRC-EMM Publications:


The JRC’s Europe Media Monitor (EMM) team carries out research and development 
in the field of highly multilingual text mining (Language Technology; 
Computational Linguistics) for the purposes of media monitoring. EMM gathers an 
average of 300,000 online news articles per day in over 70 languages and 
analyses them to help its large international user community understand and use 
this enormous amount of media information. The Europe Media Monitor EMM is 
publicly accessible and widely used. The EMM team has produced over 200 
international peer-reviewed 
publications<>. The team 
has also produced and distributes a number of highly multilingual Language 
Technology resources<>.

The Text and Data Mining Unit (I3) of the European Commission’s Joint Research 
Centre (JRC) in Ispra, Italy, is looking for a trainee to support the JRC’s 
Europe Media Monitor(EMM) team in its effort to improve its Named Entity 
Recognition and Classification (NERC) tools, especially for multi-word entities 
such as organisation and event names. EMM gathers and analyses reports from 
traditional and social media in dozens of languages by clustering related news 
items; categorising them; extracting information such as entities (persons, 
organisations, locations), events (who did what to whom, where and when), 
quotations by and about people; identifying sentiment; as well as linking 
related news clusters over time and across languages. Methods used are mostly 
hybrid: machine learning tools are used to gather evidence, learn vocabulary 
and rules, but the results are usually controlled and optimised through human 
intervention. EMM is used by European Institutions, by national authorities in 
EU Member States, by international organisations and by the public. The public 
EMM applications 
can be accessed freely by the general public. EMM is part of the JRC’s 
Competence Centre on Text Mining and Analysis.

As of now, the EMM team has implemented several approaches to multilingual 
sentiment analysis, for different text types (newspaper articles, microblogs, 
social media posts) and application scenarios (document level, short texts, 
entity-centric). The successful trainee will help to combine the current 
approaches and resources and extend them when necessary to perform multilingual 
entity and sentence-level sentiment analysis and evaluate the system thus 
obtained. The trainee is also expected to contribute to writing a scientific 
publication on the work carried out.



  *         a degree (or an almost completed degree) in computational 
linguistics, computer science or related areas;(Applications from students 
currently preparing a thesis for a University degree are eligible. The thesis 
should match with the subject of the project call).
  *            Java programming skills;
  *            good working knowledge of English. (B2 level)

  *   Experience in methods and resources for sentiment analysis and emotion 
  *   Knowledge of further foreign languages;
  *   Good knowledge of Language Technologyrelated tools and methods;
  *   Proven ability to work independently and as part of a team.


Alexandra Balahur, PhD

European Commission Joint Research Centre
Directorate I, Text and Data Mining Unit – I.3
Via E. Fermi 2749
T.P. 440
21027 Ispra (VA), Italy

Tel: +39 0332 78 5808

Disclaimer: "The views expressed in the present e-mail are only of the writer 
and may in no case be seen as stating an official position of the European 

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