Social Networking Data Analysis Tools and Services

Social Networking Data Analysis Tools and Services

Gopal Krishna
Copyright: © 2018 |Pages: 16
DOI: 10.4018/978-1-5225-5097-6.ch002
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Abstract

Social networks have drawn remarkable attention from IT professionals and researchers in data sciences. They are the most popular medium for social interaction. Online social networking (OSN) can be defined as involving networking for fun, business, and communication. Social networks have emerged as universally accepted communication means and boomed in turning this world into a global town. OSN media are generally known for broadcasting information, activities posting, contents sharing, product reviews, online pictures sharing, professional profiling, advertisements and ideas/opinion/sentiment expression, or some other stuff based on business interests. For the analysis of the huge amount of data, data mining techniques are used for identifying the relevant knowledge from the huge amount of data that includes detecting trends, patterns, and rules. Data mining techniques, machine learning, and statistical modeling are used to retrieve the information. For the analysis of the data, three methods are used: data pre-processing, data analysis, and data interpretation.
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Background

Social networking provides facilities to the users to share their views, photos, posts, videos and others contents such as their events and activities to connect with people in their network. It is similar to the inter personal social gathering in villages, markets, towns to discuss on the various issues and events.

But the main difference is that OSN enables users to connect with other users at difference locations, across the globe. Generally social networking can be noticed in different views first as which main purpose is to socializing with friends like facebook and instagram other can be networking for non-social interpersonal communication such as LinkedIn for a career and employment oriented site. So, there are many OSN sites through which people can be interlinked via cross-posting without invading the personal privacy.

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