Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm

EMNLP 2017 - Conference on Empirical Methods in Natural Language Processing, Proceedings

Volumn , Issue , 2017, Pages 1615-1625

  Felbo, Bjarke ^a   Mislove, Alan ^b   Søgaard, Anders ^c   Rahwan, Iyad ^a   Lehmann, Sune ^d  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b Northeastern University   (United States)

^c UNIVERSITY OF COPENHAGEN   (Denmark)

^d TECHNICAL UNIVERSITY OF DENMARK   (Denmark)

Author keywords

[No Author keywords available]

Indexed keywords

SENTIMENT ANALYSIS;

BENCHMARK DATASETS; DOMAIN REPRESENTATIONS; HASHTAGS; NOISY LABELS; SOCIAL MEDIA; STATE-OF-THE-ART PERFORMANCE;

BENCHMARKING;

EID: 85073167538     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.18653/v1/d17-1169     Document Type: Conference Paper

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