In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.

Input: Consider Input: We re-implement the model proposed in BIBREF3, and use it as a baseline for our problem. The rationale behind choosing this particular model as a baseline is it's proven good predictive performance on multilingual text classification.
Question: What is their baseline model?

Output: the model proposed in BIBREF3

Input: Consider Input: Stanford - Twitter Sentiment Corpus (STS Corpus): STS Corpus contains 1,600K training tweets collected by a crawler from BIBREF0 . BIBREF0 constructed a test set manually with 177 negative and 182 positive tweets. The Stanford test set is small. However, it has been widely used in different evaluation tasks BIBREF0 BIBREF5 BIBREF13 .

Sanders - Twitter Sentiment Corpus: This dataset consists of hand-classified tweets collected by using search terms: INLINEFORM0 , #google, #microsoft and #twitter. We construct the dataset as BIBREF14 for binary classification.

Health Care Reform (HCR): This dataset was constructed by crawling tweets containing the hashtag #hcr BIBREF15 . Task is to predict positive/negative tweets BIBREF14 .
Question: Which datasets did they use?

Output: Stanford - Twitter Sentiment Corpus (STS Corpus) Sanders - Twitter Sentiment Corpus Health Care Reform (HCR)

Input: Consider Input: We collected tweets related to five different DDoS attacks on three different American banks. For each attack, all the tweets containing the bank's name posted from one week before the attack until the attack day were collected. There are in total 35214 tweets in the dataset. Only the tweets from the Bank of America attack on 09/19/2012 were used in this experiment. In this subsection we evaluate how good the model generalizes. To achieve that, the dataset is divided into two groups, one is about the attacks on Bank of America and the other group is about PNC and Wells Fargo. The only difference between this experiment and the experiment in section 4.4 is the dataset. In this experiment setting $D_a$ contains only the tweets collected on the days of attack on PNC and Wells Fargo. $D_b$ only contains the tweets collected before the Bank of America attack.
Question: What is the training and test data used?
Output: Tweets related to a Bank of America DDos attack were used as training data. The test datasets contain tweets related to attacks to Bank of America, PNC and Wells Fargo.