As　a　fast　and　social　information　communication　media,　microblog,　especially　Twitter,　has　gained　increasing　popularity　in　recent　years.　Given　the　fact　that　a　great　volume　of　new　tweets　are　being　generated　every　second,　ranking　them　to　find　the　most　relevant　information　is　a　challenging　matter.　The　short　length　of　tweets　makes　direct　adoptions　of　traditional　information　retrieval　algorithms　to　microblog　search　very　hard.　In　this　paper,　we　focus　on　the　ranking　strategies　of　microblogs,　six　factors　are　summarized　to　measure　a　user＇s　social　influence,　and　each　of　them　are　highly　relevant　to　the　social　network　properties　of　the　microblog　authors　and　the　properties　of　the　microblog　itself.　Based　on　these　factors,　several　ranking　measures　for　Twitter　search　are　examined.　As　a　step　forward,　we　propose　a　weighted　multi-factor　ranking　algorithm　(WMFR).　By　using　a　public　Twitter　search　dataset,　through　Kendall＇s　τ　correlation　analysis　on　user　selection　and　algorithm　selection　of　tweets,　we　conclude　that　the　proposed　WMFR　algorithm　is　more　effective　compared　to　several　existing　algorithms.　©　2011　Springer-Verlag.