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Microblogging Comments Classification

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Swapnil Babaji Shinde, Mohammad Muzammil Shaikh, Sudeep Thepade

Swapnil Babaji Shinde, Mohammad Muzammil Shaikh and Sudeep Thepade. Microblogging Comments Classification. International Journal of Computer Applications 167(2):19-22, June 2017. BibTeX

	author = {Swapnil Babaji Shinde and Mohammad Muzammil Shaikh and Sudeep Thepade},
	title = {Microblogging Comments Classification},
	journal = {International Journal of Computer Applications},
	issue_date = {June 2017},
	volume = {167},
	number = {2},
	month = {Jun},
	year = {2017},
	issn = {0975-8887},
	pages = {19-22},
	numpages = {4},
	url = {},
	doi = {10.5120/ijca2017914177},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Nowadays, microblogging sites like, Twitter, Pinterest is used by many people to share their sentiments. These comments can be classified and analyzed to find hidden patterns. The System needs to classify these comments into various classes which can be used to find the interest of users. These interests of users will be used for giving them personalized news and also for decision making in business. Twitter tweets having a limit of 140 characters. So, people share only important comments through tweets. Using text mining most important keywords can be found from tweets and classified accordingly in multiple classes.


  1. Nirmal Jonnalagedda and Susan Gauch, Personalized News Recommendation using Twitter, IEEE, WIC and ACM conference, 2013.
  2. Shokoufeh salem minab and mehrdad jalali, Online Analyzing of Texts in Social Network of Twitter. ICTCK, 2014.
  3. Konstantinos Semertzidis, “Crawling Twitter Data”
  4. The 20 Newsgroup Dataset Classes and Instances information in detail: 20Newsgroups/
  5. Statista Twitter statistics: statistics/282087/number-of-monthly-active-twitter-users/
  6. R52 and R8 datasets :
  7. SEO Stop List :
  8. Sudeep Thepade, Dimple Parekh, Unnati Thapar, Vandana Tiwari, LBG Algorithm for Fingerprint Classification, IJAET, Nov. 2012. ISSN: 2231-1963.
  9. Dr. Sudeep Thepade, Rik Das, Saurav Ghosh, Content Based Image Classification with Thepade's Static and Dynamic Ternary Block Truncation Coding, IJER, Volume No. 4, Issue No. 1, pp: 13-17, Jan. 2017. ISSN: 2319-6890.
  10. Sagar Bhuta, Avit Doshi, Uchit Doshi, Meera Narvekar, A Review of techniques for Sentiment analysis of Twitter Data, ICICT, 2014.
  11. Andrew McCallum, Kamal Nigam, A Comparison of Event Models for Naive Bayes Text Classification.
  12. Naïve Bayes Classification with formulae – About Learning with some examples URL:


Naïve Bayes Classification, Twitter Feeds Analysis, Text Mining, News Recommendation