Statistics of temporal patterns.

<p>Statistics of temporal patterns.</p

Statistics of three types of structural motifs.

<p>Statistics of three types of structural motifs.</p

An example of diffusion network.

<p>Colors differentiate the nodes in different layers. The root node is colored in red and its large outgoing degree indicates the early popularity of the message. The large node in yellow triggers the further spread of this message.</p

Exposure curve.

<p>(a) The distribution of <i>W</i>(<i>k</i>), where <i>W</i>(<i>k</i>) denotes the number of users who are <i>k</i>-exposed to a message at certain time. (b) The distribution of <i>R</i>(<i>k</i>), where <i>R</i>(<i>k</i>) denotes the number of users who forward a message directly after being <i>k</i>-exposed to it. (c) The probability of forwarding a message as a function of the number of exposures over all cascades.</p

Temporal characteristics of information diffusion.

<p>(a) The distribution of time interval between two successive forwarding behaviors in the resolution of five minutes. (b) The distribution of time latency of message forwarding. (c) The averaged hourly activity of users.</p

Accuracy and MAPE of stock price prediction.

Accuracy and MAPE of stock price prediction.</p

Correlation coefficient between the change of stock price and the number of traders in four kinds of trading pattern on (a) 42 non-manipulated stocks and (b) 8 manipulated stocks.

Stocks are ranked in terms of correlation coefficient.</p

Evolution of number of active traders with the trading days for one randomly chosen stock.

<p>The price is presented in the upper panel and the four kinds of trading patterns in two successive days are shown in the bottom panel.</p

Statistical significance of bivariate Granger causality correlation between the change of stock price and (a) the ratio of sellers, (b) the number of sellers, and (c) the number of buyers.

For clarity, we separately show the results of manipulated stocks and non-manipulated stocks. Stocks are ranked according to the statistical significance.</p

The variation of exposure curve for different kinds of messages.

<p>(a) The probability of forwarding a message with and without embedded URL. (b) The probability of forwarding a message with and without events. (c) The probability of forwarding a message with more than one event and with a single event.</p