Clicking on the vocabulary’s namespaces (including the balloons), the user can navigate the vocabularies and get further information about them.

You can find all the information at http://labs.mondeca.com/dataset/lov/index.html

• Twitter hashtags,
• user IDs, and
• arbitrary URIs.

by a simple yet powerful syntax. For example, users can easily state that two hashtags mean the same:

#muenchen = #munich

The Hypertwitter application can extract and interpret such special tweets (Twitter messages) for two purposes, namely:

1. To expand your queries / search in Twitter (e.g. turn a query for tweets containing #muenchen into those also containing #munich), and
2. to create an RDF graph of all such statements for usage in other Web applications.

Now, given the millions of Twitter users, this could naturally lead to chaos, so there are two a simple yet effective ways to control which subset of statements should be considered:

1. Just use your own tweets.
2. Create a new public or private Twitter list that contains all users whose tweets you want us to consider. We call the list used for HyperTwitter the “trust list”.

In the simplest form, you will just trust your own statements, so you would use your Twitter ID without a list.

You can find all the information at http://semantictwitter.appspot.com/.