Paper Summary - Twitter Sentiment Classification using Distant Supervision

Twitter Sentiment Classification using Distant Supervision, A. Go and R. Bhayani and L. Huang, 2009, Technical report, Stanford Digital Library Technologies Project
This paper relates to classifying sentiment found on Twitter. They use machine learning and are able to construct training data by using the Twitter API and emoticons present among tweets. The standard :) and :( are used to determine if a tweet contains positive or negative sentiment. The key points are 1.) they picked an efficient way to construct their training sets, 2.) Tweets are harder to classify because their length can not exceed 140 characters, and 3.) their results were promising for classifying the sentiment of the tweets.