Paper Info
Title
Emotion in Code-switching Texts: Corpus Construction and Analysis
Abstract
Previous researches have focused on analyzing emotion through monolingual text, when in fact bilingual or code-switching posts are also common in social media. Despite the important implications of code-switching for emotion analysis, existing automatic emotion extraction methods fail to accommodate for the code-switching content. In this paper, we propose a general framework to construct and analyze the code-switching emotional posts in social media. We first propose an annotation scheme to identify the emotions associated with the languages expressing them in a Chinese-English code-switching corpus. We then make some observations and generate statistics from the corpus to analyze the linguistic phenomena of code-switching texts in social media. Finally, we propose a multiple-classifier-based automatic detection approach to detect emotion in the codeswitching corpus for evaluating the effectiveness of both Chinese and English texts.
Year
DOI
Venue
2015
10.18653/v1/W15-3116
SIGHAN@IJCNLP
Field
DocType
Citations 
Annotation,Social media,Code-switching,Psychology,Artificial intelligence,Natural language processing,Linguistics
Conference
6
PageRank 
References 
Authors
0.58
17
2
Name
Order
Citations
PageRank
sophia lee160.58
Zhong-qing Wang214020.28