Global Journal of Computer Sciences: Theory and Research

Yazarlar: Omer Sevinc, Iman Askerbeyli, Serdar Mehmet Guzel

Konular:-

Anahtar Kelimeler:Social web mining,Tweeter analysis,Machine learning,Text mining,Natural language processing.  

Özet: Social media has been widely used in our daily lives, which, in essence, can be considered as a magic box, providing great insights about world trend topics. It is a fact that inferences gained from social media platforms such as Twitter, Faceboook or etc. can be employed in a variety of different fields. Computer science technologies involving data mining, natural language processing (NLP), text mining and machine learning are recently utilized for social media analysis. A comprehensive analysis of social web can discover the trends of the public on any field. For instance, it may help to understand political tendencies, cultural or global believes etc. Twitter is one of the most dominant and popular social media tools, which also provides huge amount of data. Accordingly, this study proposes a new methodology, employing Twitter data, to infer some meaningful information to remarks prominent trend topics successfully. Experimental results verify the feasibility of the proposed approach.

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