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Research Article
Facebook as a Corpus for Emoticons-Based Soppiness Analysis
Dr. Pankaj S Mishra1
Asst.Prof, Smt. Tanuben & Dr. Manubhai Trivedi College of Information Science, Surat, India.
Published Online: July-August 2022
Pages: 73-76
Cite this article
No DOIReferences
[1] Alexander Hogenboom, Daniella Bal, Flavius Frasincar. Exploiting Emoticons in Sentiment Analysis.
[2] M. Taboada, K. Voll, and J. Brooke. Extracting Sentiment as a Function of Discourse Structure and Topicality. Technical
Report 20, Simon Fraser University, 2008. Available online,http://www.cs.sfu.ca/research/publications/techreports/#2008.
[3] C. Cesarano, B. Dorr, A. Picariello, D. Reforgiato, A. Sago_, and V. Subrahmanian. OASYS: An Opinio n Analysis System. In
AAAI Spring Symposium on Computational Approaches to Analyzing Weblogs (CAAW 2006), pages 21{26. AAAI Press, 2006.
[4] A. Devitt and K. Ahmad. Sentiment Polarity Identification in Financial News: A Cohesion -based Approach. In 45th Annual
Meeting of the Association of Computational Linguistics (ACL 2007), pages 984{991. Association for Computational
Linguistics,2007.
[5] X. Ding, B. Lu, and P. Yu. A Holistic Lexicon-Based Approach to Opinion Mining. In 1st ACM International Conference on Web
Search and Web Data Mining (WSDM 2008), pages 231-240. Association for Computing Machinery, 2008.
[6] B. Heerschop, F. Goossen, A. Hogenboom, F. Frasincar, U. Kaymak, and F. de Jong. Polarity Analysis of Texts using Discourse
Structure. In 20th ACM Conference on Information and Knowledge Management (CIKM 2011), pages 1061-1070. Association for
Computing Machinery, 2011.
[7] Heerschop, P. van Iterson, A. Hogenboom, F. Frasincar, and U. Kaymak. Analyzing Sentiment in a Large Set of Web Data whil e
Accounting for Negation. In 7th Atlantic Web Intelligence Conference (AWIC 2011), pages 195{205. Springer, 2011.
[8] Geetika Vashisht, Sangharsh Thakur Facebook as a Corpus for Emoticons-Based Sentiment Analysis (International Journal of
Emerging Technology and Advanced Engineering, Volume 4, Issue 5, May 2014)
[2] M. Taboada, K. Voll, and J. Brooke. Extracting Sentiment as a Function of Discourse Structure and Topicality. Technical
Report 20, Simon Fraser University, 2008. Available online,http://www.cs.sfu.ca/research/publications/techreports/#2008.
[3] C. Cesarano, B. Dorr, A. Picariello, D. Reforgiato, A. Sago_, and V. Subrahmanian. OASYS: An Opinio n Analysis System. In
AAAI Spring Symposium on Computational Approaches to Analyzing Weblogs (CAAW 2006), pages 21{26. AAAI Press, 2006.
[4] A. Devitt and K. Ahmad. Sentiment Polarity Identification in Financial News: A Cohesion -based Approach. In 45th Annual
Meeting of the Association of Computational Linguistics (ACL 2007), pages 984{991. Association for Computational
Linguistics,2007.
[5] X. Ding, B. Lu, and P. Yu. A Holistic Lexicon-Based Approach to Opinion Mining. In 1st ACM International Conference on Web
Search and Web Data Mining (WSDM 2008), pages 231-240. Association for Computing Machinery, 2008.
[6] B. Heerschop, F. Goossen, A. Hogenboom, F. Frasincar, U. Kaymak, and F. de Jong. Polarity Analysis of Texts using Discourse
Structure. In 20th ACM Conference on Information and Knowledge Management (CIKM 2011), pages 1061-1070. Association for
Computing Machinery, 2011.
[7] Heerschop, P. van Iterson, A. Hogenboom, F. Frasincar, and U. Kaymak. Analyzing Sentiment in a Large Set of Web Data whil e
Accounting for Negation. In 7th Atlantic Web Intelligence Conference (AWIC 2011), pages 195{205. Springer, 2011.
[8] Geetika Vashisht, Sangharsh Thakur Facebook as a Corpus for Emoticons-Based Sentiment Analysis (International Journal of
Emerging Technology and Advanced Engineering, Volume 4, Issue 5, May 2014)
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