The　author　interest　discovery　can　help　personalized　academic　recommendation　systems.　However,　many　topic　models　for　discovering　author　interest　implicitly　assume　equal　contribution　from　each　coauthor　to　a　target　document.　To　loosen　this　limitation,　a　novel　model,　ATcredit,　is　proposed　to　strengthen　the　Author-Topic　(AT)　model　with　an　authorship　credit　allocation　scheme,　and　the　collapsed　Gibbs　sampling　is　utilized　to　approximate　the　posterior　and　estimate　the　model　parameters.　In　total,　our　model　considers　six　counting　schemes,　including　fixed　and　flexible　versions,　as　well　as　equal　contributors　and　hyper-authorship　strategies.　©　2021,　Springer　Nature　Switzerland　AG.