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Multi-Lingual Sentiment Analysis of Social Data Based on Emotion-Bearing Patterns
2014
Proceedings of the Second Workshop on Natural Language Processing for Social Media (SocialNLP)
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 languages grows with it. However, the explosive nature of data generated around the world brings a challenge for
doi:10.3115/v1/w14-5906
dblp:conf/acl-socialnlp/ArguetaC14
fatcat:qijt4ywjmnarhaal46dzp2praq