It is proved that in text-based communication such as sms, messengers applications, misinterpretation of partner’s emotions are pretty common. In order to tackle this problem, we propose a new multilabel corpus named Emotional Movie Transcript Corpus (EMTC). Unlike most of the existing emotion corpora that are collected from Twitters and use hashtags labels, our corpus includes conversations from movie with more than 2.1 millions utterances which are partly annotated by ourselves and independent annotators. To our intuition, conversations from movies are closer to real-life settings and emotionally richer. We believe that a corpus like EMTC will greatly benefit the development and evaluation of emotion analysis systems and improve their ability to express and interpret emotions in text-based communication.
@InProceedings{DUC-ANH18.405, author = {Phan Duc-Anh and Yuji Matsumoto}, title = "{EMTC: Multilabel Corpus in Movie Domain for Emotion Analysis in Conversational Text}", booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)}, year = {2018}, month = {May 7-12, 2018}, address = {Miyazaki, Japan}, editor = {Nicoletta Calzolari (Conference chair) and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Koiti Hasida and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Hélène Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis and Takenobu Tokunaga}, publisher = {European Language Resources Association (ELRA)}, isbn = {979-10-95546-00-9}, language = {english} }
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