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ScienceDaily (May 16, 2012) In a new study analyzing Internet usage among college students, researchers at Missouri University of Science and Technology have found that students who show signs of depression tend to use the Internet differently than those who show no symptoms of depression.

Using actual Internet usage data collected from the university's network, the researchers identified nine fine-grained patterns of Internet usage that may indicate depression. For example, students showing signs of depression tend to use file-sharing services more than their counterparts, and also use the Internet in a more random manner, frequently switching among several applications.

The researchers' findings provide new insights on the association between Internet use and depression compared to existing studies, says Dr. Sriram Chellappan, an assistant professor of computer science at Missouri S&T and the lead researcher in the study.

"The study is believed to be the first that uses actual Internet data, collected unobtrusively and anonymously, to associate Internet usage with signs of depression," Chellappan says. Previous research on Internet usage has relied on surveys, which are "a far less accurate way" of assessing how people use the Internet, he says.

"This is because when students themselves reported their volume and type of Internet activity, the amount of Internet usage data is limited because people's memories fade with time," Chellappan says. "There may be errors and social desirability bias when students report their own Internet usage." Social desirability bias refers to the tendency of survey respondents to answer questions in a manner that will be viewed favorably by others.

Chellappan and his fellow researchers collected a month's worth of Internet data for 216 Missouri S&T undergraduate students. The data was collected anonymously and unobtrusively, and students involved in the study were assigned pseudonyms to keep their identities hidden from the researchers.

Before the researchers collected the usage data from the campus network, the students were tested to determine whether they showed signs of depression. The researchers then analyzed the usage data of the study participants. They found that students who showed signs of depression used the Internet much differently than the other study participants.

Chellappan and his colleagues found that depressed students tended to use file-sharing services, send email and chat online more than the other students. Depressed students also tended to use higher "packets per flow" applications, those high-bandwidth applications often associated with online videos and games, than their counterparts.

Students who showed signs of depression also tended to use the Internet in a more "random" manner -- frequently switching among applications, perhaps from chat rooms to games to email. Chellappan thinks that randomness may indicate trouble concentrating, a characteristic associated with depression.

The randomness stood out to Chellappan after his graduate student, Raghavendra Kotikalapudi, examined the "flow duration entropy" of students' online usage. Flow duration entropy refers to the consistency of Internet use during certain periods of time. The lower the flow duration entropy, the more consistent the Internet use.

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Internet usage patterns may signify depression