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?
