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Overview of NLPCC 2018 Shared Task 1: Emotion Detection in Code-Switching Text

  • Zhongqing WangEmail author
  • Shoushan Li
  • Fan Wu
  • Qingying Sun
  • Guodong Zhou
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11109)

Abstract

This paper presents the overview of the shared task, emotion detection in code-switching text, in NLPCC 2018. The submitted systems are expected to automatically determine the emotions in the Chinese-English code-switching text. Different from monolingual text, code-switching text contains more than one language, and the emotion can be expressed by either monolingual or bilingual form. Hence, the challenges are: how to integrate both monolingual and bilingual forms to detect emotion, and how to bridge the gap to between two languages. Our shared task has 19 team participants. The highest F-score was 0.515. In this paper, we introduce the task, the corpus, the participating teams, and the evaluation results.

Keywords

Emotion detection Code-switching text Annotation and evaluation 

Notes

Acknowledgment

We would like to thank the participants for their valuable feedback and results. We should thank Dr. Sophia Yat Mei Lee and Helena Yan Ping Lau for their excellent works on corpus annotation and analysis. The work is supported by the National Natural Science Foundation of China (61331011, 61751206), and the Early Career Scheme (ECS) sponsored by the Research Grants Council of Hong Kong (No. PolyU 5593/13H).

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Zhongqing Wang
    • 1
    Email author
  • Shoushan Li
    • 1
  • Fan Wu
    • 1
  • Qingying Sun
    • 1
  • Guodong Zhou
    • 1
  1. 1.Natural Language Processing LabSoochow UniversitySuzhouChina

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