In analyzing goal-oriented multiparty discussions, one challenge is to determine who is responding to whom when they are supporting or opposing a remark put forward by another participant. This paper looks at algorithms for detecting the target discussant, comparing findings of important features for three genres of text and spoken discussions. Comparing to the common baseline of “previous speaker,” we find gains from considering content and semantic similarity in target detection, but with substantial differences in accuracy and important features across genres.