Data visualization of cigarette comments from social media / Nurul Nazirah Mohamad Nasir

Cigarette is the small roll of paper that is filled with cut tobacco for smoking. Nowadays, many people use the social media to express their feeling in something, share information, give opinion or changes idea each other through the Facebook and Twitter. This study is analyze the data of cigarette...

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Bibliographic Details
Main Author: Mohamad Nasir, Nurul Nazirah
Format: Student Project
Language:English
Published: Faculty of Computer and Mathematical Sciences 2017
Subjects:
Online Access:http://ir.uitm.edu.my/id/eprint/21378/
http://ir.uitm.edu.my/id/eprint/21378/1/TD_NURUL%20NAZIRAH%20MOHAMAD%20NASIR%20M%20CS%2017_5.pdf
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Summary:Cigarette is the small roll of paper that is filled with cut tobacco for smoking. Nowadays, many people use the social media to express their feeling in something, share information, give opinion or changes idea each other through the Facebook and Twitter. This study is analyze the data of cigarettes that people comments in social media which are in Facebook, Twitter, and Google search engine. Currently, raw data extracted from the said location contains a lot of info, but mostly vague and difficult to interpret. There is a lot of data on cigarettes that people comments in social media. Then, data comments that in each word usually has same word but has different meaning. This made the task to understand the data difficult as there are no clarity regarding the comments. In order to solve these problem, the visualization will be used to present the data of cigarette. The data from social media will be match with Google correlate. All information that will be then converted into multidimensional visualization which are bubble chart and bubble cloud. To visualize the data, D3 Java library and Python server platform is employed. The preprocessing of the data is executed by using C# language. The result indicated that the visualization able to properly visualize the comments regarding cigarette effectively. Response from users shows positive feedback.