With　the　popularity　of　social　networks　and　the　increasing　number　of　micro-blog　users,　user　influence　research　has　become　a　new　topic.　PageRankhas　been　widely　used　to　measure　the　importance　of　web　pages　basedon　their　interconnections　in　the　webgraph　but　it　does　not　apply　to　social　networks.　This　paper　presents　a　new　algorithm　for　computing　the　influence　of　micro-blog　users.　According　to　the　social　network　topology,　an　iterative　factor　is　added　in　the　new　algorithm　which　is　based　on　PageRank　algorithm.　We　can　get　the　value　of　the　user＇s　influence　by　the　method　of　a　number　of　iterations　and　the　weighted　quantization.　The　results　show　that,　after　several　iterations,　each　user＇s　influence　value　will　gradually　converge.　It　tends　to　a　fixed　value　and　the　ranking　has　no　change　after　18　times　iterations.　Experimental　results　can　accurately　reflect　the　influence　of　microblog　users.