This paper proposes a novel feature for detecting anger in dialog speech. Anger is classified into two types; loud HotAnger and calm ColdAnger. Prosody can reliably detect the former but not the latter. We analyze both types of anger dialog in the two-party setting, and discover that they exhibit some differences in the temporal relation of utterances from neutral dialog. We create a dialog feature that reflects these differences, and investigate its effectiveness in detecting both types of anger. Tests show the proposed feature combination improves the F-measure of Cold and HotAnger by 24.4 points and 8.8 points against baseline technique that uses only prosody.