Thesis:

Identifying and prioritizing the effective factors of virtual space on students' attitudes with fuzzy Dematel method and network analysis process

The current research is titled "Identification and prioritization of the effective factors of virtual space on students' attitude with fuzzy Dematel method and network analysis process" in the period of 1403. The statistical population of this research is formed by the number of 433 male and female high school students of Sabzevar city, and the questionnaire was designed based on the information provided by the researcher. Therefore, the research method based on the nature and data collection is a descriptive survey type and in terms of the goal, it is an applied development. This research was conducted with the aim of identifying and prioritizing the effective factors of virtual space on the social attitude and behavior of students using the Fuzzy Dimetal method and the process of network analysis. The results of this research show that the effect of virtual space on the social attitude and behavior of students is a complex and multidimensional phenomenon. Many factors play a role in it. Based on the fuzzy DANP analysis, it was found that respect in the family is the most important factor in this regard. This finding shows that the family still has a central role in shaping the attitude and behavior of students in the digital age. A healthy family environment and relationships based on respect can act as a protective shield against the possible negative effects of cyberspace and help students to use this space in a constructive and useful way. Religious beliefs were ranked second in importance, which indicates the important role of religious beliefs and values in the way students interact with cyberspace. This finding can reflect the cultural and social context of the studied society and shows how religious beliefs can act as a guiding framework for students in how to use virtual space and interpret its content.

Keywords: virtual space, social behavior, students, fuzzy model, network analysis network analysis