Identifying and Classification Users Behaviors in Social Networks

Background and Aim: Social networks with many users uses different services. These users provide information concerning social behaviors and their networks upon their routine activities with regard to interests. In social networks and web environment, one of the methods for social and user behavior researches are based on users request or express interest to one or more case or a special classification of services but in the other hand users will not perform their routine activities in terms of initial registered interests. Methods In this research, we examine two factors of user behavior in social networks and expression of interests subjects and on basis that, according to clustered algorithms and classified algorithms with multi-layer neural network, based on user's interests list and his/her behavior in social networks environment he/she is placed in a new cluster and classification and in terms of new conditions, some effective services is recognized for him/her or expert machines. Results: One goal is to find the consistency of the user's behavior and the favorites that users mentioned or selected, and depending on the severity of the match, the content will be presented and so This content can be targeted socially, economically, politically, and so on. The other goal is to find the severity of the mismatch of favorite lists with user behaviors and its relation to social conditions in social sciences and behavioral science studies. Conclusion Under the new classification, a number of meaningful behaviors can be acquired from the people who are being studied that not necessarily announcing them or even consciously or unconsciously avoiding them in public announcement; According to political, cultural, religious, economic and social conditions, there is a contradiction between his behavior and his interests. From a social and cognitive science point of view, the severity of the discrepancy between interest lists and behavior can be indicative of the extent to which the subject is accepted or, in contrast, avoided by the community. In this case, the users change his/her behavior according to the general condition of society under the influence of the positive or negative reaction of the community. Based on the information obtained from the new classification, specific and targeted clinical materials can be designed and the results can be used in widely distributed cognitive models or to help solve the patient's health problems. In this case, the patient is not affected by laboratory conditions such as EEG equipment, monitors and room conditions.

کلیدواژه ها:

Identifying ، Classification ، Users Behaviors ، Social Networks ، Neural Network ، Social Behaviors ، Social and Cognitive Science