We address the issue of intertemporal topic correlations in a selection of online media consisting of political weblogs and press website content. We wish to investigate in which way various information sources may be correlated, therefore preceding and maybe influencing each other. We use hidden Markov modeling to exhibit dynamic relationships in topic occurrences between distinct groups of weblogs; thereby considering topic distributions over weblog groups as system states, looking for minimal causal states, and exhibiting their transition probabilities. Beyond behavioral correlations between some groups of blogs and online media, we also identify varied and richer types of inter-group patterns. In particular, using a very compact description, we could infer interpretations as to how diverse groups of blogs behave with respect to each other as regards raising and discussing issues.