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.
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Question: In our experiments, we used TF.IDF-based features over the title and over the content of the article we wanted to classify. We had these features twice – once for the title and once for the the content of the article, as we wanted to have two different representations of the same article. Thus, we used a total of 1,100 TF.IDF-weighted features (800 content + 300 title), limiting the vocabulary to the top 800 and 300 words, respectively (which occurred in more than five articles). 
 Question: what lexical features did they experiment with?

Answer: TF.IDF-based features


Question: We also measure the usage of words related to people's core values as reported by Boyd et al. boyd2015. The sets of words, or themes, were excavated using the Meaning Extraction Method (MEM) BIBREF10 . 
 Question: How do they obtain psychological dimensions of people?

Answer: using the Meaning Extraction Method


Question: Figure 1 shows a simple linear model with rank constraint. 
 Question: What are their baseline methods?

Answer:
simple linear model with rank constraint Hierarchical softmax N-gram features