Franciska de Jong
Franciska de Jong
Universiteit Utrecht/Erasmus Universiteit/Universiteit Twente
Verified email at - Homepage
Cited by
Cited by
Improving cyberbullying detection with user context
M Dadvar, D Trieschnigg, R Ordelman, F De Jong
Advances in Information Retrieval: 35th European Conference on IR Research …, 2013
Exploiting emoticons in sentiment analysis
A Hogenboom, D Bal, F Frasincar, M Bal, F De Jong, U Kaymak
Proceedings of the 28th annual ACM symposium on applied computing, 703-710, 2013
Computational sociolinguistics: A survey
D Nguyen, AS Doğruöz, CP Rosé, F De Jong
Computational linguistics 42 (3), 537-593, 2016
Improved cyberbullying detection using gender information
M Dadvar, FMG de Jong, R Ordelman, D Trieschnigg
Proceedings of the Twelfth Dutch-Belgian Information Retrieval Workshop (DIR …, 2012
An Overview of Event Extraction from Text.
F Hogenboom, F Frasincar, U Kaymak, F De Jong
DeRiVE@ ISWC, 48-57, 2011
Care more about customers: Unsupervised domain-independent aspect detection for sentiment analysis of customer reviews
A Bagheri, M Saraee, F De Jong
Knowledge-Based Systems 52, 201-213, 2013
MeSH Up: effective MeSH text classification for improved document retrieval
D Trieschnigg, P Pezik, V Lee, F De Jong, W Kraaij, ...
Bioinformatics 25 (11), 1412-1418, 2009
A survey of pre-retrieval query performance predictors
C Hauff, D Hiemstra, F de Jong
Proceedings of the 17th ACM conference on Information and knowledge …, 2008
Polarity analysis of texts using discourse structure
B Heerschop, F Goossen, A Hogenboom, F Frasincar, U Kaymak, ...
Proceedings of the 20th ACM international conference on Information and …, 2011
A survey of event extraction methods from text for decision support systems
F Hogenboom, F Frasincar, U Kaymak, F De Jong, E Caron
Decision Support Systems 85, 12-22, 2016
Experts and machines against bullies: A hybrid approach to detect cyberbullies
M Dadvar, D Trieschnigg, F De Jong
Advances in Artificial Intelligence: 27th Canadian Conference on Artificial …, 2014
Why gender and age prediction from tweets is hard: Lessons from a crowdsourcing experiment
D Nguyen, D Trieschnigg, AS Dogruöz, R Gravel, M Theune, T Meder, ...
COLING 2014, 25th International Conference on Computational Linguistics …, 2014
Compositional Translation
MT Rosetta, ps., L Appelo, T Janssen, F de Jong, J Landsbergen, ( eds.).
Kluwer, 1994
Cyberbullying detection: a step toward a safer internet yard
M Dadvar, F De Jong
Proceedings of the 21st International Conference on World Wide Web, 121-126, 2012
Generalized quantifiers: the properness of their strength
F De Jong, H Verkuyl
Rijksuniv., Instituut de Vooys 1, 21-43, 1984
Multi-lingual support for lexicon-based sentiment analysis guided by semantics
A Hogenboom, B Heerschop, F Frasincar, U Kaymak, F de Jong
Decision support systems 62, 43-53, 2014
Temporal Language Models for the Disclosure of Historical Text
FMG de Jong, H Rode, D Hiemstra
AHC (History and Computing), 161-169, 2005
Scope of negation detection in sentiment analysis
M Dadvar, C Hauff, FMG De Jong
11th Dutch-Belgian Information Retrieval Workshop, DIR 2011, 16-20, 2011
Exploiting emoticons in polarity classification of text
A Hogenboom, D Bal, F Frasincar, M Bal, F De Jong, U Kaymak
Journal of Web Engineering, 022-040, 2015
ADM-LDA: An aspect detection model based on topic modelling using the structure of review sentences
A Bagheri, M Saraee, F De Jong
Journal of Information Science 40 (5), 621-636, 2014
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