Content marketing through data mining on Facebook social network
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As the Internet has found its place within different sectors of society, the use of various social networks is increasing and that is why they are utilized for business purposes. Most commercial companies need to do marketing in social networks in order to introduce their goods and/or services. In marketing, appropriate and accurate advertisement of goods based on needs of users of these social networks is required to sell the goods of different companies and manufacturing units in effective ways. In most cases, however, advertising and marketing methods in social networks are not correct and the resulted advertisements are boring and tiring to users and they might ignore them without noticing. Such advertisements will be considered as spam and will be annoying to network users. This is taken into consideration in the present study where users' interests, attitudes, and behavior on Facebook are specified through data mining techniques, based on which content marketing is conducted. The present study is conducted on the social network of Facebook, where content marketing, a new form of marketing, is utilized and instead of introducing the goods, the contents of different goods are presented. The data utilized in the study are actual and related to Facebook users, and therefore, the results can be generalized to other networks.