Papers

 

1. You are strongly encouraged to submit a short system description paper by February 27, 2017. For submission intructions, formatting, FAQ, etc. please check the general SemEval-2017 webpage.

 

2. You can write a paper regardless of whether you plan to attend SemEval-2017 at Vancouver (registration for SemEval-2017 and participation are optional, but strongly encouraged). Your paper will be published even if you do not register for SemEval-2017 (provided that reviewers find it to be of acceptable quality).

 

3. For your paper, you are allowed to use 4 pages, excluding references. However, if you have participated in more than one subtask, you can use up to 6 pages (excluding references).


4. There is no need to describe the task in much detail, as you can point to the system description paper instead (BibTex below), which will contain a detailed description of the corpora and subtasks, together with an overall discussion of the results and participant systems. You can concentrate on the description of your system and experiments. Please, make sure to use the exact following BibTex citation for the task description paper. We will cite back your system description paper in the task description paper:

@InProceedings{SemEval:2017:task4,
  author    = {Sara Rosenthal and Noura Farra and Preslav Nakov},
  title     = {{SemEval}-2017 Task 4: Sentiment Analysis in {T}witter},
  booktitle = {Proceedings of the 11th International Workshop on Semantic Evaluation},
  series    = {SemEval '17},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
}

Contact Info

  • Sara Rosenthal, IBM Research
  • Noura Farra, Columbia University
  • Preslav Nakov, Qatar Computing Research Institute, HBKU
email: semevaltweet@googlegroups.com

Other Info

Announcements

  • Results, and gold labels are released
  • Arabic and English TEST INPUT v1.0 for phase 2 (subtasks B, D) released
  • Arabic and English TEST INPUT v3.0 for phase 1 (subtasks A, C, E) released
  • Arabic and English training data released
  • CodaLab development sets on Data and Tools page