Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Automated Detection of Doxing on Twitter   Doxing refers to the practice of disclosing sensitive personal information
about a person without their consent. This form of cyberbullying is an
unpleasant and sometimes dangerous phenomenon for online social networks.
Although prior work exists on automated identification of other types of
cyberbullying, a need exists for methods capable of detecting doxing on Twitter
specifically. We propose and evaluate a set of approaches for automatically
detecting second- and third-party disclosures on Twitter of sensitive private
information, a subset of which constitutes doxing. We summarize our findings of
common intentions behind doxing episodes and compare nine different approaches
for automated detection based on string-matching and one-hot encoded
heuristics, as well as word and contextualized string embedding representations
of tweets. We identify an approach providing 96.86% accuracy and 97.37% recall
using contextualized string embeddings and conclude by discussing the
practicality of our proposed methods.

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The categories of this paper are: math-ph
15
The categories of this paper are: nucl-ex
21
The categories of this paper are: adap-org
37
The categories of this paper are: supr-con
34
The categories of this paper are: chem-ph
11
The categories of this paper are: hep-lat
27
The categories of this paper are: comp-gas
26
The categories of this paper are: bayes-an
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The categories of this paper are: astro-ph
9
The categories of this paper are: nlin
0
The categories of this paper are: hep-ph
29
The categories of this paper are: funct-an
30
The categories of this paper are: q-alg
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The categories of this paper are: cond-mat
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The categories of this paper are: eess
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The categories of this paper are: dg-ga