Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Towards Business Partnership Recommendation Using User Opinion on
  Facebook   The identification of strategic business partnerships can potentially provide
competitive advantages for businesses; however, due to the dynamics and
uncertainty present in business environments, this task could be challenging.
To help businesses in this task, this study presents a similarity model between
businesses that consider the opinions of users on content shared by businesses
on social media. Thus, this model captures significant virtual relationships
among businesses that are generated by users in the virtual world. Besides, we
propose an algorithm for detecting business communities in the considered
model. We also propose an algorithm to identify possible business outliers in
the detected communities, which could represent an automatic way to identify
non-obvious relations that might deserve particular attention of business
owners. By exploring approximately 280 million user reactions on Facebook, we
show that our results could favor the development of, for example, a new
strategic business partnership recommendation service.

37
The categories of this paper are: supr-con
18
The categories of this paper are: econ
22
The categories of this paper are: chao-dyn
4
The categories of this paper are: cond-mat
16
The categories of this paper are: stat
35
The categories of this paper are: mtrl-th
28
The categories of this paper are: alg-geom
9
The categories of this paper are: nlin
20
The categories of this paper are: acc-phys
19
The categories of this paper are: eess
30
The categories of this paper are: q-alg
2
The categories of this paper are: math
31
The categories of this paper are: ao-sci
34
The categories of this paper are: chem-ph
36
The categories of this paper are: cmp-lg
32
The categories of this paper are: atom-ph