OMSA

opinion mining and sentiment analysis

Approaches

• Supervised
• Unsupervised
• Semi-supervised

Key words

• Methods:k-NN, NB, ME, SVM
• Terms: frequency, tf/idf, cosine distance, similarity

References:

• Supervised NB approach: http://karpathy.ca/mlsite/lecture2.php
• Supervised kNN approach: http://karpathy.ca/mlsite/lecture3.php
• Full comprehensive NLTK site: http://streamhacker.com/
• Twitter, discovering customer insight: http://www.jucs.org/jucs_18_8/discovering_consumer_insight_from/jucs_18_08_0973_0992_chamlertwat.pdf
• Good starting: http://andybromberg.com/sentiment-analysis-python/?utm_source=Python+Weekly+Newsletter&utm_campaign=c15c89a350-Python_Weekly_Issue_75_February_21_2013&utm_medium=email
• Twitter, handson SA: http://ravikiranj.net/drupal/201205/code/machine-learning/how-build-twitter-sentiment-analyzer
• Will it Python, Machine Learning for hackers: http://slendrmeans.wordpress.com/will-it-python/