  Quantitative study of collective dynamics in online social networks is a new
challenge based on the abundance of empirical data. Conclusions, however, may
depend on factors as user's psychology profiles and their reasons to use the
online contacts. In this paper we have compiled and analyzed two datasets from
\texttt{MySpace}. The data contain networked dialogs occurring within a
specified time depth, high temporal resolution, and texts of messages, in which
the emotion valence is assessed by using SentiStrength classifier. Performing a
comprehensive analysis we obtain three groups of results: Dynamic topology of
the dialogs-based networks have characteristic structure with Zipf's
distribution of communities, low link reciprocity, and disassortative
correlations. Overlaps supporting "weak-ties" hypothesis are found to follow
the laws recently conjectured for online games. Long-range temporal
correlations and persistent fluctuations occur in the time series of messages
carrying positive (negative) emotion. Patterns of user communications have
dominant positive emotion (attractiveness) and strong impact of circadian
cycles and nteractivity times longer than one day. Taken together, these
results give a new insight into functioning of the online social networks and
unveil importance of the amount of information and emotion that is communicated
along the social links. (All data used in this study are fully anonymized.)
