@InProceedings{lozic-EtAl:2017:SemEval,
  author    = {Lozi\'{c}, David  and  \v{S}ari\'{c}, Doria  and  Toki\'{c}, Ivan  and  Medi\'{c}, Zoran  and  \v{S}najder, Jan},
  title     = {TakeLab at SemEval-2017 Task 4: Recent Deaths and the Power of Nostalgia in Sentiment Analysis in Twitter},
  booktitle = {Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {784--789},
  abstract  = {This paper describes the system we submitted to SemEval-2017 Task 4 (Sentiment
	Analysis in Twitter), specifically subtasks A, B, and D. Our main focus was
	topic-based message polarity classification on a two-point scale (subtask B).
	The system we submitted uses a Support Vector Machine classifier with rich set
	of features, ranging from standard to more creative, task-specific features,
	including a series of rating-based features as well as features that account
	for sentimental reminiscence of past topics and deceased famous people. Our
	system ranked 14th out of 39 submissions in subtask A, 5th out of 24
	submissions in subtask B, and 3rd out of 16 submissions in subtask D.},
  url       = {http://www.aclweb.org/anthology/S17-2132}
}