Twitter Orographies is an experiment in the visualization of Twitter conversations targeting the discussion space 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).
Once the final network is defined, the interface creates a semantic landscape out of the discussion, in which the most relevant topics appear as higher mountains and the emerging topics as lower hills, and where the relatedness is mapped to topic proximity and displayed through the use of explicit visual links.
The orographic metaphor allows to track the evolution of smaller and bigger landforms that represent specific topics, mountain systems that display clusters of related topics, orografic belts created by chains of given words (usually caused by pseudo-retweets).