Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Assessing Viewer's Mental Health by Detecting Depression in YouTube
  Videos   Depression is one of the most prevalent mental health issues around the
world, proving to be one of the leading causes of suicide and placing large
economic burdens on families and society. In this paper, we develop and test
the efficacy of machine learning techniques applied to the content of YouTube
videos captured through their transcripts and determine if the videos are
depressive or have a depressing trigger. Our model can detect depressive videos
with an accuracy of 83%. We also introduce a real-life evaluation technique to
validate our classification based on the comments posted on a video by
calculating the CES-D scores of the comments. This work conforms greatly with
the UN Sustainable Goal of ensuring Good Health and Well Being with major
conformity with section UN SDG 3.4.

37
The categories of this paper are: supr-con
14
The categories of this paper are: math-ph
18
The categories of this paper are: econ
6
The categories of this paper are: astro-ph
29
The categories of this paper are: funct-an
15
The categories of this paper are: nucl-ex
23
The categories of this paper are: solv-int
36
The categories of this paper are: cmp-lg
16
The categories of this paper are: stat
20
The categories of this paper are: acc-phys
11
The categories of this paper are: hep-lat
8
The categories of this paper are: hep-ex
24
The categories of this paper are: dg-ga
27
The categories of this paper are: comp-gas
7
The categories of this paper are: hep-th
12
The categories of this paper are: nucl-th