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International Journal of Advanced Engineering, Management and Science


Customer Behavior Analysis for Social Media

( Vol-3,Issue-1,January 2017 )

Author(s): S. D. Kularathne, R.B. Dissanayake, N.D. Samarasinghe, L.P.G. Premalal, S. C. Premaratne



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Page No: 011-021
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Keywords:

Machine Learning, Natural Language Processing, Word Sense Disambiguation, Sentiment Analysis, Trend Analysis, Forecasting, Opinion Prediction, Association Rule Mining .

Abstract:

It is essential for a business organization to get the customer feedback in order to grow as a company. Business organizations are collecting customer feedback using various methods. But the question is ‘are they efficient and effective?’ In the current context, there is more of a customer oriented market and all the business organizations are competing to achieve customer delight through their products and services. Social Media plays a huge role in one’s life. Customers tend to reveal their true opinion about certain brands on social media rather than giving routine feedback to the producers or sellers. Because of this reason, it is identified that social media can be used as a tool to analyze customer behavior. If relevant data can be gathered from the customers’ social media feeds and if these data are analyzed properly, a clear idea to the companies what customers really think about their brand can be provided.

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