Multi-emotion Detection in User-Generated Reviews

Expressions of emotion abound in user-generated content, whether it be in blogs, reviews, or on social media. Much work has been devoted to detecting and classifying these emotions, but little of it has acknowledged the fact that emotionally charged text may express multiple emotions at the same time. We describe a new dataset of user-generated movie reviews annotated for emotional expressions, and experimentally validate two algorithms that can detect multiple emotions in each sentence of these reviews.

[1]  Grigorios Tsoumakas,et al.  On the Stratification of Multi-label Data , 2011, ECML/PKDD.

[2]  Arthur C. Graesser,et al.  Predicting Affective States expressed through an Emote-Aloud Procedure from AutoTutor's Mixed-Initiative Dialogue , 2006, Int. J. Artif. Intell. Educ..

[3]  Cecilia Ovesdotter Alm,et al.  Emotions from Text: Machine Learning for Text-based Emotion Prediction , 2005, HLT.

[4]  Rafael A. Calvo,et al.  Affect Detection: An Interdisciplinary Review of Models, Methods, and Their Applications , 2010, IEEE Transactions on Affective Computing.

[5]  Grigorios Tsoumakas,et al.  Multi-Label Classification of Music into Emotions , 2008, ISMIR.

[6]  Sunita Sarawagi,et al.  Discriminative Methods for Multi-labeled Classification , 2004, PAKDD.

[7]  Sampo Pyysalo,et al.  brat: a Web-based Tool for NLP-Assisted Text Annotation , 2012, EACL.

[8]  Gaël Varoquaux,et al.  Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..

[9]  Shady Shehata,et al.  Enhancing Search Engine Quality Using Concept-based Text Retrieval , 2007, IEEE/WIC/ACM International Conference on Web Intelligence (WI'07).

[10]  Stan Szpakowicz,et al.  Identifying Expressions of Emotion in Text , 2007, TSD.

[11]  Bo Pang,et al.  A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts , 2004, ACL.

[12]  P. Shaver,et al.  Emotion knowledge: further exploration of a prototype approach. , 1987, Journal of personality and social psychology.

[13]  Hsin-Hsi Chen,et al.  Emotion Classification Using Web Blog Corpora , 2007, IEEE/WIC/ACM International Conference on Web Intelligence (WI'07).

[14]  Roman Grundkiewicz,et al.  Automatic Extraction of Polish Language Errors from Text Edition History , 2013, TSD.

[15]  P. Shaver,et al.  Emotion knowledge: further exploration of a prototype approach. , 1987 .

[16]  Chih-Jen Lin,et al.  LIBLINEAR: A Library for Large Linear Classification , 2008, J. Mach. Learn. Res..

[17]  Gilles Louppe,et al.  Independent consultant , 2013 .

[18]  T. Danisman,et al.  Feeler: Emotion Classification of Text Using Vector Space Model , 2008 .

[19]  Grigorios Tsoumakas,et al.  Multi-Label Classification: An Overview , 2007, Int. J. Data Warehous. Min..

[20]  Peter A. Flach,et al.  Evaluation Measures for Multi-class Subgroup Discovery , 2009, ECML/PKDD.

[21]  Grigorios Tsoumakas,et al.  Random k -Labelsets: An Ensemble Method for Multilabel Classification , 2007, ECML.

[22]  Carlo Strapparava,et al.  SemEval-2007 Task 14: Affective Text , 2007, Fourth International Workshop on Semantic Evaluations (SemEval-2007).

[23]  Joost N. Kok.  Machine Learning: ECML 2007, 18th European Conference on Machine Learning, Warsaw, Poland, September 17-21, 2007, Proceedings , 2007, ECML.

[24]  E. Tan.  Emotion and the structure of narrative film , 1996 .

[25]  Carlo Strapparava,et al.  Learning to identify emotions in text , 2008, SAC '08.