Microblogging Comments Classification

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. General Terms Information Retrieval, Classification

[1]  Huan Liu,et al.  Crawling Twitter Data , 2014 .

[2]  Mehrdad Jalali,et al.  Online analyzing of texts in social network of Twitter , 2014, 2014 International Congress on Technology, Communication and Knowledge (ICTCK).

[3]  Meera Narvekar,et al.  A review of techniques for sentiment analysis Of Twitter data , 2014, 2014 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT).

[4]  Saurav Ghosh,et al.  Content Based Image Classification with Thepade's Static and Dynamic Ternary Block Truncation Coding , 2015 .

[5]  Susan Gauch,et al.  Personalized News Recommendation Using Twitter , 2013, 2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT).

[6]  Andrew McCallum,et al.  A comparison of event models for naive bayes text classification , 1998, AAAI 1998.