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The financial system, a complex network, operates primarily through the exchange of capital, where the role of information is critical. This study utilizes the transfer entropy method to examine the strength and direction of information flow among different capital flow time series and investigate the community structure within the transfer networks. Moreover, the spreading dynamics of the capital flow transfer networks are observed, and the importance and traveling time of each node are explored. The results imply a dominant role for the food and drink industry within the Chinese market, with increased attention towards the computer industry starting in 2014. The community structure of the capital flow transfer networks significantly differs from those constructed from stock prices, with the main sector predominantly encompassing industry leaders favored by primary funds with robust capital flow connections. The average traveling time from sectors such as food and drink, coal, and utilities to other sectors is the shortest, and the dynamic flow between these sectors displays a significant role. These findings highlight that comprehension of information flow and community structure within the financial system can offer valuable insights into market dynamics and help to identify key sectors and companies. [ABSTRACT FROM AUTHOR]

With data from epitaphs of elites in ancient China, we construct the elite social networks of the Tang-dynasty and the Song-dynasty. The complexity theory is then introduced to unveil associations between the elite social networks and the history. The top influential elites in ancient China are identified from the elite social networks. We detect the community structure formed with strongly connected elites, and investigate the interactions between the communities. It is observed that the elite social networks of the Tang-dynasty and the Song-dynasty exhibit the neutral and disassortative mixing patterns, respectively. Additionally, this work quantitatively supports the Tang-Song Transition Hypothesis. • Reconstruct the elite social networks (ESNs) of ancient China. • Identify the top influential elites in ancient China. • Unveil the community structure of the ESNs. • Present the neutral and disassortative patterns in the ESNs. [ABSTRACT FROM AUTHOR]