Analyzing the Language of Food on Social Media
TABLE VIII: Effects of varying the fraction of tweets used for training and testing on classification accuracy in the state-prediction task, using All Words and LDA topics.
['training fraction', 'testing fraction 0.2', 'testing fraction 0.4', 'testing fraction 0.6', 'testing fraction 0.8', 'testing fraction 1.0']
Performance varies from 11.76% when using 20% of tweets in the training set and 20% in the testing set, to 64.7% when using all available tweets. Increasing the number of tweets in the training set has a larger positive effect on accuracy than increasing the number of tweets in the testing set. As in the city prediction task, performance continues to increase as we add more data, suggesting that the performance ceiling has not been reached.