Exploring Big Data with Social Media Analytics Essay

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Today, over 5 billion people have mobile phones, 2 billion people are on the Internet, an individual spends more than 3 hours online, and over 400 million tweets are sent per day. 2.5 billion contents are shared on Facebook, 2.7 billion “Likes”; 300 million photos are being uploaded. Facebook is the world´s largest community serving over a billion of users. Social media are storing massive amount of data of terabytes to zettabytes size, never-before-analyzed data that carry crucial information, which cannot be ignored. However, around 90% of the captured data is “Unstructured” meaning it's spontaneously generated and not easily captured and classified. The graph below shows the voluminous increase of unstructured data from 2010 to 2015. …show more content…

5. Social Media Analytics and Complexity. Data in Social Media comes from numerous sources. It is a great challenge to use different processes like linking, matching, connecting, correlating relationships, hierarchies and multiple data linkages. This is how complex data can be and if not managed properly, could go out of control.( Ref 2)
Data Analytics
In social media every user actively produces data, either by Googling, by sharing tweets, comments, profiles, favorites, likes or follows, or by uploading or downloading blogs, photos, videos or such other content. The amount of information that gets into the Internet is unimaginable large and predicted to double every 18 months. Every single action on the social media produces added value, which can be aggregated and capitalized in commercial advertising and market analysis. This is how companies such as Google and Facebook have been able to become multibillion-dollar businesses.

“Facebook ingests approximately 500 times more data each day than the New York Stock Exchange (NYSE). Twitter is storing at least 12 times more data each day than the NYSE” according to research. (Ref 3)

Lot of researches and studies are being conducted in analyzing this data and “Data Analytics” has become a subject by itself. Data mining processes great potential, as the data has predictive power; the

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