The　carbon　footprint　embodied　in　international　population　mobility　has　a　complex　spatial　correlation,　which　exacerbates　the　difficulty　of　global　climate　governance.　However,　the　features,　changing　trends,　and　determinants　of　the　carbon　footprint　flow　embodied　in　global　population　migration　are　poorly　understood.　This　study　employed　social　network　analysis　and　the　exponential　random　graph　model　(ERGM)　to　investigate　the　structural　changes　and　drivers　of　the　carbon　footprint　network　embodied　in　global　migration　from　1995　to　2015.　The　results　showed　that　approximately　50%　of　carbon　footprint　flow　embodied　in　international　migration　flowed　from　developing　to　developed　countries.　The　spatial　connections　between　countries　in　the　network　were　becoming　increasingly　close,　displaying　a　typical　small　-world　structure,　and　showing　low　reciprocity　and　negative　assortativity.　Moreover,　centrality　analysis　highlighted　the　United　States　and　the　European　Union　as　being　at　the　core　of　the　network,　whereas　some　emerging　economies　(e.g.,　China,　India,　and　South　Africa)　were　shown　as　having　an　increasing　influence　on　the　network.　The　determinants　of　network　formation　were　divided　into　three　effects.　For　node　attribute　effect,　countries　with　developed　economy,　high　proportion　of　industrial　value　added,　urbanization　and　openness　were　becoming　the　destinations　of　carbon　inflows　from　immigrants,　while　countries　with　high　consumption　of　renewable　energy　and　energy　intensity　had　a　trend　of　carbon　outflows　with　emigrants　over　periods.　As　for　exogenous　network　effect,　the　significance　of　economic　integration　on　the　formation　of　the　network　was　strengthening,　while　that　of　geographical　proximity　and　cultural　similarity　was　declining.　Additionally,　the　positive　impact　of　self　-organizational　effect　on　the　network　was　decreasing.　This　study　provided　guidance　for　countries　to　formulate　policies　to　reduce　the　carbon　emissions　embodied　in　international　migration.