Recently, it was demonstrated many times that the fractal properties vary from point to point along the series, leading to multifractality. Human heart rate variability, in the form of time series of intervals between heart beats, shows complex, fractal properties. The obtained initial results have shown that the assembled methodology for bioelectrical signals' recording and analysis might be a valuable tool for the study of impact of social networks on human emotions and facilitation of IT developments assessment and control in the information society. The spectral nature of the studied signals suggests correlation with the emotions of the Facebook users. We tried to assemble an ad-hoc methodology for exploring emotions of a Facebook pilot group of users implementing time-frequency spectral analysis (based on S-transform) and rhythm dynamics characteristics representation of a complex set of recorded bioelectrical signals with parallel psychometric tests. The study of human emotions by means of bioelectrical signals and psychometrics has a long history, but the data for an influence of Web-based social networks is still scarce and specific methods are lacking. The emerging social networks like Facebook and Twitter with their huge popularity produce a strong impact to our life.
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