Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Fake Cures: User-centric Modeling of Health Misinformation in Social
  Media   Social media's unfettered access has made it an important venue for health
discussion and a resource for patients and their loved ones. However, the
quality of the information available, as well as the motivations of its
posters, has been questioned. This work examines the individuals on social
media that are posting questionable health-related information, and in
particular promoting cancer treatments which have been shown to be ineffective
(making it a kind of misinformation, willful or not). Using a multi-stage user
selection process, we study 4,212 Twitter users who have posted about one of
139 such "treatments", and compare them to a baseline of users generally
interested in cancer. Considering features capturing user attributes, writing
style, and sentiment, we build a classifier which is able to identify users
prone to propagate such misinformation at an accuracy of over 90%, providing a
potential tool for public health officials to identify such individuals for
preventive intervention.

36
The categories of this paper are: cmp-lg
16
The categories of this paper are: stat
23
The categories of this paper are: solv-int
28
The categories of this paper are: alg-geom
5
The categories of this paper are: gr-qc
4
The categories of this paper are: cond-mat
21
The categories of this paper are: adap-org
2
The categories of this paper are: math
26
The categories of this paper are: bayes-an
0
The categories of this paper are: hep-ph
34
The categories of this paper are: chem-ph
9
The categories of this paper are: nlin
32
The categories of this paper are: atom-ph
13
The categories of this paper are: quant-ph
35
The categories of this paper are: mtrl-th
11
The categories of this paper are: hep-lat