The purpose of this study was to predict addiction to virtual networks based on feelings of loneliness, communication skills, social intelligence and emotional intelligence. The research method was descriptive-correlation. The statistical population of the study consist
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The purpose of this study was to predict addiction to virtual networks based on feelings of loneliness, communication skills, social intelligence and emotional intelligence. The research method was descriptive-correlation. The statistical population of the study consisted of all high school students of Isfahan city in the academic year of 1979-1999 with a total number of about 36,000. 380 individuals (161 males and 194 females) were selected as the sample of the study using Morgan and Krejcie's table by multistage cluster sampling. In order to collect data from the EHQ Mobile Affiliate Questionnaires (1395), Dietomaso et al. (2004), Barton's Communication Skills (1990), Silva et al.'s Social Intelligence (2001), Emotional Intelligence Siberia Shering (1996) was used. Multivariate regression analysis was used to analyze the data. The results of data analysis showed that there is a positive and significant relationship between emotional intelligence and addiction to virtual networks and a negative relationship between communication skills and feelings of loneliness with addiction to virtual networks. Emotional intelligence has the greatest power to predict addiction to virtual networks. There was a positive relationship between social loneliness and addiction to virtual networks, while there was a negative relationship between family loneliness and feedback skills with addiction to virtual networks and a positive and significant relationship between self-awareness, self-regulation and empathy with addiction to virtual networks. Overall, feelings of loneliness, weak communication skills, social intelligence, and low emotional intelligence can increase students' addiction to virtual networks.
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