Paper: Multi-Lingual Sentiment Analysis of Social Data Based on Emotion-Bearing Patterns

ACL ID W14-5906
Title Multi-Lingual Sentiment Analysis of Social Data Based on Emotion-Bearing Patterns
Venue Workshop on Natural Language Processing for Social Media
Session  
Year 2014
Authors

Social networking sites have flooded the Internet with posts containing shared opinions, moods, and feelings. This has given rise to a new wave of research to develop algorithms for emotion detection and extraction on social data. As the desire to understand how people feel about certain events/objects across countries or regions grows, the need to analyze social data in different lan- guages grows with it. However, the explosive nature of data generated around the world brings a challenge for sentiment-based information retrieval and analysis. In this paper, we propose a multilingual system with a computationally inexpensive approach to sentiment analysis of so- cial data. The experiments demonstrate that our approach performs an effective multi-lingual sentiment analysis of microblog dat...

@InProceedings{argueta-chen:2014:SocialNLP,
  author    = {Argueta, Carlos  and  Chen, Yi-Shin},
  title     = {Multi-Lingual Sentiment Analysis of Social Data Based on Emotion-Bearing Patterns},
  booktitle = {Proceedings of the Second Workshop on Natural Language Processing for Social Media (SocialNLP)},
  month     = {August},
  year      = {2014},
  address   = {Dublin, Ireland},
  publisher = {Association for Computational Linguistics and Dublin City University},
  pages     = {38--43},
  url       = {http://www.aclweb.org/anthology/W14-5906}
}