instruction:
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.
question:
To account for sequences of words and characters that might carry useful information, we extracted word unigrams, bigrams, and trigrams as features. 
 Question: Which features do they use to model Twitter messages?
answer:
word unigrams, bigrams, and trigrams


question:
To compare our results, we use the provided baseline, which is a non-parameter optimized linear-kernel SVM that uses TF-IDF bag-of-word vectors as inputs.  
 Question: What was the baseline model?
answer:
a non-parameter optimized linear-kernel SVM that uses TF-IDF bag-of-word vectors as inputs


question:
For every gendered character in the dataset, we ask annotators to create a new character with a persona of the opposite gender that is otherwise identical except for referring nouns or pronouns. 
 Question: In the targeted data collection approach, what type of data is targetted?
answer:

Gendered characters in the dataset