What goes on behind the scenes at social networking websites?

The Truth Behind Social Networking Websites Part1. The Usual Suspects" About this part: In this part some statistics which give a general idea about the magnitude of internet and social media usage. The social networks mentioned here are not perse the largest but we restricted our- selves mentioning the most common social networking sites, which are active on a global scale. Google+ registered users 1,600,000,000 Facebook registered users 1,280,000,000 Twitter registered users 9 3, 8 0 0, 0 0 0 iLinkedin registered users 200,00 0,000 39% 30% percentage of world population 16% using the internet: 74% internetusers who use social networks (jan. 14) 2005 2010 2013 Part 2. Big Brothers Friend: Big Data 1 Context Targeting Optimizing business processes possible applications By obtaining personal information from social media, advertising agencies are able to target customers with specific advertising, which is custom fit according to the interpretation of the personal information available on that individial. Organisations are able to optimize processes better. For example: - Based on buy behaviour of customers over time it is possible to adjust the way stock is managed in a more effective and cost reductive way. Organisations are able to anticipate on fluc- tuations better which increases overall efficiency and logistics. with big data via use of personal information The advertising is targetted on the customer in the appropriate context. Behaviour 5prediction 4 Applications for Eovernments Big Data analysis is able (still in an early stage) to predict customer behaviour. Possi- bilities of this functionality are gigantic. Governments can use big data of personal infor- mation to optimize their cities or countrie more efficiently (p.e. infrastructural). Secondly they are able to increase the succesrate of security and law enforcement. One good example of this is prediction of possible crime locations in a city based on behaviour prediction. Examples: -The case where a super- market predicted that a teen daughter was pregnant based on her purschases of less strong smelling shampoo (see article below infographic) - overall prediction of pos- by the year 2020: definton Big bata 40.000 exabytes sible milestones in a persons urne of structured and definition 'Big Data' life, like marriage, purchasing a car or divorce. Our digital universe will reach 40k exabytes in 2020. A single exabyte contains 50,000 years' worth of DVD-quality video. "an enormous volume of structured and unstructured data which is so large that it is difficult to process with the use of tradition database and software techn es." Part 3. The Lifestories Trade-ofF What is Social Networking websites sell your personal information to organisations and governments. At this point in time there is little to na legislation about who owns the actual rights of this information, or to whom the information can or cannot be sotd to. The question is if the actual rights of this personal informa- your personat information EWorth: tion should belong to the particular individual, instead of the social media networking websites. Another question is if there should be more legislation about which organisations social media can sell the information to. Without proper laws there could be room for abusal of this information in the future. More awareness about this will create an opportunity for a public debate. Average lifestory price: <$1,00 p/p (information about wealthier then average individuals is more expensive) information: $0,0005 per person information: $ 0,50 per 1000 price of a milestone: $ 0,26 (becoming a parent, moving, divorce, purchasing car, health conditions) Price for a persons general Price for a persons general <$1,00 per average lifestory $0,0005 $0,50 $0,26 for general personal information per 1000 persons per įndividual mílestone (C) 2014, dé Seo Content Specialist [ website: seocontentspecialist.nl]-[ Twitter: aPaper_Mountainz]-[email [email protected]]-[facebook.com/decontentspecialist]