Twitter Crowd Mining and Data Fishing
Sherin Eliyas1, R. Naveen2, M. Siva Krishna3
1Sherin Eliyas, MCA, School of Computing Science, Hindustan Institute of Technology and Science, Rajiv Gandhi Salai, Padur, Chennai (Tamil Nadu), India.
2R. Naveen, MCA, School of Computing Science, Hindustan Institute of Technology and Science, Rajiv Gandhi Salai, Padur, Chennai (Tamil Nadu), India.
3M. Siva Krishna, MCA, School of Computing Science, Hindustan Institute of Technology and Science, Rajiv Gandhi Salai, Padur, Chennai (Tamil Nadu), India.
Manuscript received on 04 June 2019 | Revised Manuscript received on 29 June 2019 | Manuscript Published on 04 July 2019 | PP: 411-415 | Volume-8 Issue-1S4 June 2019 | Retrieval Number: A10740681S419/2019©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: People use twitter as a medium to share their opinions, which in turn makes it a platform for analyzing public opinion. This kind of information in various fields can be used for further analysis. Text mining is used for classifying tweets into negative and positive statements depending on their purpose. Text messages are used to define mind set of large groups of people. From perspective of decision makers, precious information is provided by collection of text messages. In this paper, we use data collected from twitter and extract useful data from it using data mining tools. The results is represented as decision trees and this can be used to make further analysis or used to take decision for analyst. Here we evaluate or analyze the impact of tweets by using emotic icons for process.
Keywords: Twitter, Crowd Mining, Data Fishing.
Scope of the Article: Data Mining