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 To run label propagation using [[http://code.google.com/p/junto/|Junto]]'s implementation of Modified Adsorption on the Stanford Sentiment dataset, use the following command:
 
 {{{
-$ updown 8 junto -g data/stanford/stanford-features.txt -m models/maxent-eng.mxm -p src/main/resources/eng/lexicon/subjclueslen1polar.tff -f data/stanford/username-username-edges.txt -r src/main/resources/eng/model/ngramProbs.ser.gz 
+$ updown 8 junto -g data/stanford/stanford-features.txt -m models/maxent-eng.mxm -p
+    src/main/resources/eng/lexicon/subjclueslen1polar.tff -f data/stanford/username-username-edges.txt -r src/main/resources/eng/model/ngramProbs.ser.gz 
 }}}
 
 (Note that this currently requires more than 4 gigabytes of memory (the '8' above indicates that 8 are used) due to the way the unigram and bigram probabilities are stored. We plan on improving the space efficiency of this in the future. You can run the label propagation with less memory by eliminating the -r flag and its argument, but results will not be as good.)
 By default, all five of these are included, i.e. adding "-e nfmoe" to the above command line would not change output. To run on just the follower graph and EmoMaxent's predictions, for example, you would add "-e fm" to the command line, like so:
 
 {{{
-updown 8 junto -g data/stanford/stanford-features.txt -m models/maxent-eng.mxm -p src/main/resources/eng/lexicon/subjclueslen1polar.tff -f data/stanford/username-username-edges.txt -r src/main/resources/eng/model/ngramProbs.ser.gz -e fm
+updown 8 junto -g data/stanford/stanford-features.txt -m models/maxent-eng.mxm -p
+    src/main/resources/eng/lexicon/subjclueslen1polar.tff -f data/stanford/username-username-edges.txt -r src/main/resources/eng/model/ngramProbs.ser.gz -e fm
 }}}
 
 You should see the following output: