Discovering influential users based on sensitive for enhancing social media relationship management

Recently Customer relationship management (CRM) improved by social media. Social media is a key factor for user’s decision buying because it is fastest and easiest method to distribute user’ idea and information and also companies canimprove their advertising, decrease the cost of advertising and increase profits. This paper aims to analyze user’s post on social media and predict user’s sentiment for discovering influentialusers. Influential users who diffuse information and their followers have interest to this information finally they can maximize diffusion in social networks. Influential users explain their sentiments rather than a subject so they can attract orexpellant follower. We proposed a method for analyzing user’s post and user’s actions. These methods called SIU that include of preprocess data, extraction stem, extraction user’s action andprediction user’s sentiment rather than product or service. We used FACE BOOK network with 400 users and 3985 post for evaluating of SIU method and compared performance SIUmethod with other two methods. SIU method has accuracy and recall better than other two methods. Finally SIU method extract user’s idea and predict user’s sentiment to a product and serviceand also monitors the social networks to obtain a growing rate of customer’s interaction and also identify in a more efficient way the opportunities/leads that come through these channels.

Keywords:

social media , social customer relationship management (SCRM) , text mining , stemming , opinion