EOI: 10.11242/viva-tech.01.01.06

Download Full Text here


Vinit N. Tendulkar, Rahul M. Sonavane, Prashish R. Kamble, Sunita Naik, "SURVEY ON CARD LESS TRANSACTION USING EMERGING TECHNOLOGIES", VIVA-Tech IJRI Volume 1, Issue 1, Article 6, pp. 1-6, Oct 2018. Published by Computer Engineering Department, VIVA Institute of Technology, Virar, India.


The latest generation of emoticons which are called as emojis that is largely being used in mobile communications as well as in social media. In past few years, more than ten billion emojis were used on Twitter. Emojis which are known as the Unicode graphic symbols, which are basically used as shorthand to express the concepts and ideas of the people. For smaller number of well-known emoticons, their meanings or sentiments are well known but there are thousands of emojis so extracting their sentiments is difficult. The Emoji Sentiment Ranking method which is used to evaluate a sentiment mapping of emojis by using sentiment polarity such as negative, neutral, or positive. The sentimental classification of tweets with and without emoticons are very much different.Finally, the method also gives representation of sentiments and a better visualization in the form of a sentimental Bar.


Classification of Emoticons, Emoji Sentiment Ranking, Sentiment Bar, Sentiment labels, Sentiment score.


  1. S. Georgios, K. N. Vavliakis, and P. A. Mitkas, "Multilingual Sentiment analysis using emoticons and keywords", Web Intelligence (WI) and Intelligent Agent Technologies (IAT), 2014 IEEE/WIC/ACM International Joint Conferences on. Vol. 2. IEEE, 2014.
  2. N. Najeeb, and S. Jamal. "A Survey on Mining User Opinion from Texts and Emoticons."
  3. J. Fei, "Microblog sentiment analysis with emoticon space model", Journal of Computer Science and Technology 30.5 (2015), pp. 1120-1129.
  4. A. Hogenboom, "Exploiting emoticons in sentiment analysis." Proceedings of the 28th Annual ACM Symposium on Applied Computing, ACM, 2013.
  5. Amalanathan, Anthoniraj, and S. Margret Anouncia. "Social network user’s content personalization based on emoticons." Indian Journal of Science and Technology 8.23 (2015).
  6. M. Hasan, E. Rundensteiner, and E. Agu. "Emotex: Detecting emotions in twitter messages." (2014).
  7. B. Heerschop, F. Goossen, A. Hogenboom, F. Frasincar, U. Kaymak, and F. de Jong. “Polarity Analysis of Texts using Discourse Structure”. 20th ACM Conference on Information and Knowledge Management (CIKM 2014), pp. 1061-1070.Association for Computing Machinery, 2014.
  8. Ip Amy. "The impact of emoticons on affect interpretation in instant messaging." Retrieved April 26 (2002): 2014.
  9. Zhou, Rui, Jasmine Hentschel, and Neha Kumar. "Goodbye Text, Hello Emoji: Mobile Communication on WeChat in China." Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. ACM, 2017.
  10. Tchokni, SimoEditha, Diarmuid O. Séaghdha, and Daniele Quercia. "Emoticons and Phrases: Status Symbols in Social Media." ICWSM. 2014.
  11. N. N. Bazarova "Social sharing of emotions on Facebook: Channel differences, satisfaction, and replies." Proceedings of the 18th ACM Conference on Computer Supported cooperative Work & Social Computing. ACM, 2015.
  12. A. Sarlan, C. Nadam, and S. Basri. "Twitter sentiment analysis." Information Technology and Multimedia (ICIMU), 2014 International Conference on. IEEE, 2014.