Summary of the paper
| Title | Emotion Cause Events: Corpus Construction and Analysis |
|---|---|
| Authors | Sophia Yat Mei Lee, Ying Chen, Shoushan Li and Chu-Ren Huang |
| Abstract | Emotion processing has always been a great challenge. Given the fact that anemotion is triggered by cause events and that cause events are an integral partof emotion, this paper constructs a Chinese emotion cause corpus as a firststep towards automatic inference of cause-emotion correlation. The corpusfocuses on five primary emotions, namely happiness, sadness, fear, anger, andsurprise. It is annotated with emotion cause events based on our proposedannotation scheme. Corpus data shows that most emotions are expressed withcauses, and that causes mostly occur before the corresponding emotion verbs. Wealso examine the correlations between emotions and cause events in terms oflinguistic cues: causative verbs, perception verbs, epistemic markers,conjunctions, prepositions, and others. Results show that each group oflinguistic cues serves as an indicator marking the cause events in differentstructures of emotional constructions. We believe that the emotion cause corpuswill be the useful resource for automatic emotion cause detection as well asemotion detection and classification. |
| Language | Text mining |
| Topics | Corpus (creation, annotation, etc.), Emotion Recognition/Generation, Text mining |
Full paper  |
Emotion Cause Events: Corpus Construction and Analysis |
| Bibtex | @InProceedings{LEE10.322, author = {Sophia Yat Mei Lee, Ying Chen, Shoushan Li and Chu-Ren Huang}, title = {Emotion Cause Events: Corpus Construction and Analysis}, booktitle = {Proceedings of the Seventh conference on International Language Resources and Evaluation (LREC'10)}, year = {2010}, month = {may}, date = {19-21}, address = {Valletta, Malta}, editor = {Nicoletta Calzolari (Conference Chair), Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odjik, Stelios Piperidis, Mike Rosner, Daniel Tapias}, publisher = {European Language Resources Association (ELRA)}, isbn = {2-9517408-6-7}, language = {english} } |