Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Knowledge Acquisition from Social Platforms Based on Network
  Distributions Fitting   The uniqueness of online social networks makes it possible to implement new
methods that increase the quality and effectiveness of research processes.
While surveys are one of the most important tools for research, the
representativeness of selected online samples is often a challenge and the
results are hardly generalizable. An approach based on surveys with
representativeness targeted at network measure distributions is proposed and
analysed in this paper. Its main goal is to focus not only on sample
representativeness in terms of demographic attributes, but also to follow the
measures distributions within main network. The approach presented has many
application areas related to online research, sampling a network for the
evaluation of collaborative learning processes, and candidate selection for
training purposes with the ability to distribute information within a social
network.

7
The categories of this paper are: hep-th
5
The categories of this paper are: gr-qc
2
The categories of this paper are: math
15
The categories of this paper are: nucl-ex
35
The categories of this paper are: mtrl-th
21
The categories of this paper are: adap-org
28
The categories of this paper are: alg-geom
36
The categories of this paper are: cmp-lg
24
The categories of this paper are: dg-ga
22
The categories of this paper are: chao-dyn
25
The categories of this paper are: patt-sol
11
The categories of this paper are: hep-lat
20
The categories of this paper are: acc-phys
17
The categories of this paper are: q-fin
16
The categories of this paper are: stat
14
The categories of this paper are: math-ph