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Risk correlation is an important topic in software development. This study applied meta-analysis to both collect risk checklists and compose a natural language description set of 1932 sentences. Co-word analysis was performed to obtain a word co-occurrence matrix. The correlation network features were then analyzed in the form of a social network. Characters including density, centrality, distance and core/periphery were put forward about the risk correlation network. The high frequency risk word list and related network conclusions are helpful for software risk management.