In this paper, we introduce the first dataset that records the news co-mention relationships in the Chinese A-share market. In total, we collected 1,138,247 pieces of news articles that at least mentioned one listed firm in the A market from major Chinese media and financial websites from September 1999 to December 2022. The development of this dataset could enable data scientists and financial economists to investigate the network of stocks through news co-mention in the Chinese stock market. The dataset could also help to construct novel portfolio strategies like the cross-firm momentum strategy with news-implied links as in Ge et al. (2023).

This paper decomposes news-implied linkages into two types: leader-follower links (LF) and peer links (PE), based on people's reading and information-processing habits. We explore how the structure of information impacts processing costs and subsequently leads to market outcomes by examining momentum spillover effects via these distinct linkage types. Our findings indicate that the information structure of leader-follower links is more readily comprehensible to investors than peer linkages. We provide empirical evidence of this by demonstrating faster attention spillover from leader to follower than among peer firms, using Baidu search data. Furthermore, we document that due to the lower information processing cost, information transmits through the leader-follower linkages more quickly, leading to a weaker momentum spillover effect compared to the more complex and less easily perceivable peer links.