The　correlations　between　financial　firms　have　a　significant　impact　on　the　emergence　and　spread　of　systemic　financial　risks.　In　addition　to　traditional　numerical　data,　text　data　also　contains　a　lot　of　relational　information　and　could　serve　as　a　data　source　for　unveiling　cross-firm　relationships.　This　paper　uses　news　data　to　construct　a　co-occurrence　network　of　Chinese　financial　firms　and　subsequently　employs　the　Louvain　algorithm　to　detect　communities,　showing　clusters　of　firms　with　dense　interconnections.　Relationships　among　firms　are　further　examined　from　a　community　perspective.　The　results　demonstrate　that　firms　within　the　same　industry　have　a　greater　degree　of　interconnections　in　the　co-occurrence　network.　Besides,　the　level　of　correlation　between　communities　fluctuates　in　response　to　shocks　and　policies.　©　2023　The　Authors.　Published　by　Elsevier　B.V.　This　is　an　open　access　article　under　the　CC　BY-NC-ND　license　(https://creativecommons.org/licenses/by-nc-nd/4.0)　Peer-review　under　responsibility　of　the　scientific　committee　of　the　Tenth　International　Conference　on　Information　Technology　and　Quantitative　Management.