Extracting Ironic Tweets using Experts Model

Author:

Yeruva Nagamani1ORCID,Venna Sarada1ORCID,Indukuri Hemalatha2ORCID,Marreddy Mounika3ORCID

Affiliation:

1. JNTU Kakinada, India

2. Information Technology, SRKR ENGINEERING COLLEGE (A), India

3. LTRC, IIIT Hyderabad, India

Publisher

ACM

Reference43 articles.

1. Using Stylometric Features for Sentiment Classification

2. Stefano Baccianella , Andrea Esuli , and Fabrizio Sebastiani . 2010 . Sentiwordnet 3.0: An enhanced lexical resource for sentiment analysis and opinion mining . In Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC’10) . Stefano Baccianella, Andrea Esuli, and Fabrizio Sebastiani. 2010. Sentiwordnet 3.0: An enhanced lexical resource for sentiment analysis and opinion mining. In Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC’10).

3. Modelling Sarcasm in Twitter, a Novel Approach

4. Aspect Based Recommendations

5. Christos Baziotis Nikos Athanasiou Pinelopi Papalampidi Athanasia Kolovou Georgios Paraskevopoulos Nikolaos Ellinas and Alexandros Potamianos. 2018. NTUA-SLP at SemEval-2018 Task 3: Tracking Ironic Tweets using Ensembles of Word and Character Level Attentive RNNs. CoRR abs/1804.06659(2018). arxiv:1804.06659 Christos Baziotis Nikos Athanasiou Pinelopi Papalampidi Athanasia Kolovou Georgios Paraskevopoulos Nikolaos Ellinas and Alexandros Potamianos. 2018. NTUA-SLP at SemEval-2018 Task 3: Tracking Ironic Tweets using Ensembles of Word and Character Level Attentive RNNs. CoRR abs/1804.06659(2018). arxiv:1804.06659

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