A study on the new approaches for social network based recommendations in digital marketing

Social interactions can be inferred on the web using the mailing list and home page links. It also represents the social lives of the individuals, collaborations, communities and relationship. Social networking groups are becoming increasingly important due to the volume and activities. Thus, the structure of the network, connectivity, movement of members from one group to another and change of interest are important for further investigation. Users on social networking websites maintain an explicit, self-craft run-down of their own interest and zeal, mentioned using free-form natural language. The main focus of this work is to find out the information hub or influential node which has large number of contacts in Online Social Network and recommends relevant advisement so that the product or service reaches a vast number of friends or users within the advertisement budget.