Addiction-Based Tenuous Community Detection in Online Social Media

In the last decades, more social media users have been connected to the corrosion and decrease of face-to-face communication. Increasing the number of social network interactions, such as cyber-based relationship addiction and constant dependence on online social media, has been noted to become tenuous in real life. In this paper, we challenge that extraction of online behavior and real-life behavior gives us a tenuous relationship in real life. We conducted a problem-based scenario to collect data to find the range of people with social media addiction and vulnerable relationships. We use the degree and distance centrality closeness algorithm (DADCC) to find a community using social media, not live without online social media, and also find a community that uses social media but is not highly abdicated. However, both types of communities create a tenuous relationship with each other. We explore the importance of real life, but people’s relationship with real life becomes tenuous, for example, by constantly checking Facebook updates or tracking people for hours. There is no direct conclusion to define whether a person is a social media addict; however, many doctors have found similar symptoms such as depression, anxiety, and psychological disorders, which are evidence of social media addiction. The main purpose of our work is to indicate that people’s involvement in real life is much more beneficial as compared to online-based work.