============================================================================== Linking to Yelp dataset (via a symlink)

ln -s $HOME/Dropbox/sentiment-data/yelp/ yelp

============================================================================== Toolkits

Oliver Mason's Qtag program [http://phrasys.net/uob/om/software]

============================================================================== For setting up Maximum Entropy Modeling Toolkit for Python and C++

Main page [http://homepages.inf.ed.ac.uk/lzhang10/maxent_toolkit.html] Source [https://github.com/lzhang10/maxent] Wonderful documentation, except for the missing Python API reference [http://homepages.inf.ed.ac.uk/lzhang10/software/maxent/manual.pdf]

DEPENDENCIES zlib [http://www.techsww.com/tutorials/libraries/zlib/installation/installing_zlib_on_ubuntu_linux.php] libboost [apt-get] jam [apt-get]

Important points

• L-BFGS is the default parameter estimating method in this toolkit.

============================================================================== Preprocess movie data

Use Qtag with the "underscore" and "process all files in directory" options $ java -jar qtag.jar

Move the POS tagged data out to its own directory, for further processing $ mv pos/tagged/ pos_tagged $ mv neg/tagged/ neg_tagged

Tag data with position $ python position_tagger.py -d pos $ python position_tagger.py -d neg

Filter out for only adjectives $ python adjectives_filter.py -d neg $ python adjectives_filter.py -d pos

Filter out for only verbs $ python verb_filter.py -d pos $ python verb_filter.py -d neg

============================================================================== Preprocess Yelp data

Make yelp data look like movie data in terms of formatting, and limit to 1000 per star rating $ python preprocess_yelp.py -d yelp/default/1star_limited $ python preprocess_yelp.py -d yelp/default/2star_limited $ python preprocess_yelp.py -d yelp/default/3star_limited $ python preprocess_yelp.py -d yelp/default/4star_limited $ python preprocess_yelp.py -d yelp/default/5star_limited

Use Qtag with the "underscore" and "process all files in directory" options $ java -jar qtag.jar

Move the POS tagged data out to its own directory, for further processing $ mv 1star_limited/tagged/ 1star_limited_tagged $ mv 2star_limited/tagged/ 2star_limited_tagged $ mv 3star_limited/tagged/ 3star_limited_tagged $ mv 4star_limited/tagged/ 4star_limited_tagged $ mv 5star_limited/tagged/ 5star_limited_tagged

Tag data with position $ python position_tagger.py -d yelp/default/1star_limited $ python position_tagger.py -d yelp/default/2star_limited $ python position_tagger.py -d yelp/default/3star_limited $ python position_tagger.py -d yelp/default/4star_limited $ python position_tagger.py -d yelp/default/5star_limited

Filter out for only adjectives $ python adjectives_filter.py -d yelp/default/1star_limited $ python adjectives_filter.py -d yelp/default/2star_limited $ python adjectives_filter.py -d yelp/default/3star_limited $ python adjectives_filter.py -d yelp/default/4star_limited $ python adjectives_filter.py -d yelp/default/5star_limited

Filter out for only verbs $ python verb_filter.py -d yelp/default/1star_limited $ python verb_filter.py -d yelp/default/2star_limited $ python verb_filter.py -d yelp/default/3star_limited $ python verb_filter.py -d yelp/default/4star_limited $ python verb_filter.py -d yelp/default/5star_limited