György Csepeli: Mental Health and Social Network
- 1. György Csepeli Mental Health and Social Network TÁMOP Belső képzés 2014 IX.24
- 3. Coping with ἄπειρον • Brownian movement, any of various physical phenomena in which some quantity is constantly undergoing small, random fluctuations • When sharks and other ocean predators can’t find food, they abandon Brownian motion. The data showed that the so called Lévy flights can describe the animals' hunting patterns. • Efficient routing in a network can be performed by links having a Levy flight length distribution.
- 4. Scale-fee networks Albert László Barabási, Péter Csermely “Matthew effect” (Mt.25.29) „For unto every one that hath shall be given, and he shall have abundance: but from him that hath not shall be taken even that which he hath. Complex systems (mental and social networks) Few connection rich elements (hubs) Many connection poor elements (nods) Robustness to failure The ability to regenerate Clustering (Homogeneity)
- 5. Internet as a new medium of human life • Access to the internet anytime, anywhere with anybody about anything • Traces left behind • Analysis and diagnosis based on the traces • Facebook behavior (moves of action) • Creating content, sharing, commenting • Pressing the button “like”
- 6. The study • Can we infer about the state of mind of a person on the basis of traces they had left on Facebook? • We assumed that the data distribution of the activity of people logging on Facebook can be analyzed in terms of the scale free pattern • Periods of rest and activity were to be analyzed • 195 respondents, volunteers • Coauthor: Richard Nagyfi
- 10. Data collection • Beck’s Depresssion Inventory measuring level of stress and anxiety • An automatic data mining algorith was running on the user’s computer enabling us to collect aggregated information abozt the user’s past acivity on Facebook
- 11. Analysis • Comparison of the results of the Questionnaira and the activity data of Facebook presence • Correlation found between the activity curve of presence on Facebook and the result of the questionnaire • Scale free distribution corresponded with lack of depression, stress and anxiety • Anxiety, stress measured by the questionnaire were reflected on the digressions of the curve from the scale-free patter
- 12. Social network effects • No indication of mental health problem was found isolated • The disorder showed up in the network of the Facebook user • The ‘friends’ of Facebook users had shown the same pattern of activity indicating their mental status • The “friends” of healthy users are typically healthy
- 13. Questions Can be the individual mental disorder states distinguished by typifying the non scale free distributions? How different are the patterns of social network of the mentally disordered and mentally ill people? How can we instruct the mentally ill people to detect their mental status and to help them to selfmonitoring and to orient them to ask for professional help?