Job Title: Judge emotions about weather from Twitter  The CrowdFlower sentiment data asks the rater to judge the sentiment of a tweet discussing the weather. The data is comprised of 98,979 tweets. Each tweet was evaluated by at least 5 raters, for a total of approximately 500,000 answers. For more descriptions about the data, you can refer to the webpage.  The possible answers are:  1 Negative 2 Neutral / author is just sharing information 3 Positive 4 Tweet not related to weather condition 5 I can't tell  Dataset: Each tweet has been preprocessed to a feature vector with 43, 397 features based on the TFIDF techniques. Since each feature corresponds to one word, the feature vector is very sparse. That is, most of the feature values are zero and only very few non-zero features are available for each tweet. For each tweet, the answer which is consistent with most raters is recognized as the ground-truth answer. Your objective is to generate the best possible answer for each tweet.