Generating, Refining and Using Sentiment Lexicons

  • Maarten de Rijke
  • Valentin Jijkoun
  • Fons Laan
  • Wouter Weerkamp
  • Paul Ackermans
  • Gijs Geleijnse
Part of the Theory and Applications of Natural Language Processing book series (NLP)


In order to use a sentiment extraction system for a media analysis problem, a system would have to be able to determine which of the extracted sentiments are relevant, i.e., it would not only have to identify targets of extracted sentiments, but also decide which targets are relevant for the topic at hand.



In addition to funding by the STEVIN programme, this research was also partially supported by the European Union’s ICT Policy Support Programme as part of the Competitiveness and Innovation Framework Programme, CIP ICT-PSP under grant agreement nr 250430, the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreements nr 258191 (PROMISE Network of Excellence) and 288024 (LiMoSINe project), the Netherlands Organisation for Scientific Research (NWO) under project nrs 612.061.814, 612.061.815, 640.004.802, 380-70-011, 727.011.005, the Center for Creation, Content and Technology (CCCT), the Hyperlocal Service Platform project funded by the Service Innovation & ICT program, the WAHSP project funded by the CLARIN-NL program, under COMMIT project Infiniti and by the ESF Research Network Program ELIAS.


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Copyright information

© The Author(s) 2013

Open Access. This chapter is distributed under the terms of the Creative Commons Attribution Noncommercial License, which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.

Authors and Affiliations

  • Maarten de Rijke
    • 1
  • Valentin Jijkoun
    • 2
  • Fons Laan
    • 1
  • Wouter Weerkamp
    • 1
  • Paul Ackermans
    • 3
  • Gijs Geleijnse
    • 3
  1. 1.ISLA, University of AmsterdamAmsterdamNetherlands
  2. 2.Textkernel BVAmsterdamNetherlands
  3. 3.Philips Research EuropeEindhovenNetherlands

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