In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.

[Q]: We show that by determining and integrating heterogeneous set of features from different modalities aesthetic features from posted images (colorfulness, hue variance, sharpness, brightness, blurriness, naturalness), choice of profile picture (for gender, age, and facial expression), the screen name, the language features from both textual content and profile's description (n-gram, emotion, sentiment), and finally sociability from ego-network, and user engagement we can reliably detect likely depressed individuals in a data set of 8,770 human-annotated Twitter users.
[A]: What is the source of the user interaction data?

[Q]: We downloaded 76 videos from a tutorial website about an image editing program .
[A]: What is the source of the triples?

[Q]: The Software Ontology (SWO) BIBREF5 is included because its set of CQs is of substantial size and it was part of Ren et al.'s set of analysed CQs. The CQ sets of Dem@Care BIBREF8 and OntoDT BIBREF9 were included because they were available. CQs for the Stuff BIBREF6 and African Wildlife (AWO) BIBREF7 ontologies were added to the set, because the ontologies were developed by one of the authors (therewith facilitating in-depth domain analysis, if needed), they cover other topics, and are of a different 'type' (a tutorial ontology (AWO) and a core ontology (Stuff)), thus contributing to maximising diversity in source selection.
[A]:
How many domains of ontologies do they gather data from?