Twitter Orographies is an experiment in the visualization of Twitter conversations. Built on top of previous experiments, this interfaces aims to represent the discussion space of around a given keyword. It represents the semantic space of topics that emerge, the relative relevance of each topic, and the relations between the different topics that arise from the discussion.
Operationally, Twitter Orographies works by listening (in real time) to the stream of all the tweets that mention a given keyword (or hashtag). Each one of these tweets is then analyzed by removing common words with weak semantic content (such as articles and propositions) and the remaining words are added to a weighted network in which the discussion topics are represented by nodes (weighted by frequency) and weight of the edges represent the relatedness of the topics (how often the two topics appear in the same tweet).
On the representation level, the network is once again filtered, and the interface shows only the topics that reach a given threshold in a given amount of time (eg. topics cited at least twice in the last five minutes). …
