With　the　increasing　scale　of　literature　publication　and　the　rapid　growth　in　the　number　of　publications,　topic　extraction　methods　have　also　made　great　progress,　yet　the　extent　to　which　the　topic　extraction　results　reflect　the　true　subject　structure　of　the　scientific　literature　remains　an　open　question.　In　the　development　of　topic　extraction,　the　validity　of　topic　extraction　results　has　been　an　issue　of　concern　to　scholars.　This　paper　contributes　to　validating　the　topic　extraction　method　by　using　an　external　validation　method　to　evaluate　the　topic　extraction　results.　Considering　that　each　piece　of　literature　may　involve　more　than　one　research　topic,　this　thesis　completes　topic　extraction　using　four　overlapping　community　detection　algorithms,　COPRA,　DEMON,　SLPA,　and　GCE,　based　on　direct　citation　network　construction.　The　topic　extraction　results　were　then　investigated　for　validation　with　the　help　of　external　metadata　as　the　validation　dataset.　©　2023　IEEE.