Stop propagation of harmful information on social networks

Information propagation in social networks is a fast and efficient process irrespective of helpful or harmful information. There exists a practical interest of stopping propagation of harmful information to save reputation of companies from deteriorating. Companies can immunize a person who has received harmful information by approaching to the person with anti harmful information. Moreover companies can not take any mass approaching measures because that may acknowledge the people who have not received harmful information about previous existance of harmful information. Hence companies can stop whole propagation by convincing all the persons who have recieved the harmful information but have not yet spreaded. The problem is to find out a list of minimum number of persons, approaching to whom can stop the propagation. In this paper we map this problem to a graph theoretic problem and we develop an algorithm that finds out desired list of minimum number of persons that isolates the information propagators from all the persons who have not received the harmful information.