Given the task definition and input, reply with output. In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.

We create the graph using all data, and training set tweets have an initial language label distribution. A naive approach to building the tweet-tweet subgraph requires O( INLINEFORM0 ) comparisons, measuring the similarity of each tweet with all others. Instead, we performed INLINEFORM1 -nearest-neighbour classification on all tweets, represented as a bag of unigrams, and compared each tweet and the top- INLINEFORM2 neighbours. We use Junto (mad) BIBREF5 to propagate labels from labelled to unlabelled nodes. Upon convergence, we renormalise label scores for initially unlabelled nodes to find the value of INLINEFORM4 .
Question: How are labels propagated using this approach?
We use Junto (mad) BIBREF5 to propagate labels from labelled to unlabelled nodes.