Cities　are　the　main　contributors　to　carbon　dioxide　emissions,　and　communities　are　crucial　for　implementing　urban　low-carbon　emissions.　As　a　result　of　the　controversies　surrounding　existing　transformation　technologies　and　the　varying　conditions　faced　by　different　targets　for　transformation,　an　effective　method　is　required　for　application　in　specific　target　communities　to　achieve　good　carbon　reduction　effects.　We　propose　a　method　that　utilizes　the　knowledge　graph　and　scenario　analysis　to　systematically　screen　and　evaluate　community　low-carbon　technologies.　First,　a　comprehensive　knowledge　map　spanning　multiple　fields　was　constructed,　and　the　correlations　were　analyzed　using　CiteSpace.　Additionally,　we　categorized　the　transformation　technologies　into　nine　scenarios　to　assess　their　effectiveness　and　feasibility　across　different　community　contexts.　Finally,　the　near-zero　carbon　emission　community　pilot　area　of　Shenzhen　City　was　selected　as　a　case　study,　and　the　method　was　applied　as　a　demonstration.　The　total　carbon　emissions　of　the　pilot　community　were　reduced　by　43%　after　applying　the　proposed　method.　This　method　is　helpful　for　technical　screening　at　the　low-carbon　transformation　stage　and　also　provides　a　useful　reference　for　the　low-carbon　construction　stage　of　communities.