Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Method and Analysis to Elicit User-reported Problems in Intelligent
  Everyday Applications   The complex nature of intelligent systems motivates work on supporting users
during interaction, for example through explanations. However, as of yet, there
is little empirical evidence in regard to specific problems users face when
applying such systems in everyday situations. This paper contributes a novel
method and analysis to investigate such problems as reported by users: We
analysed 45,448 reviews of four apps on the Google Play Store (Facebook,
Netflix, Google Maps and Google Assistant) with sentiment analysis and topic
modelling to reveal problems during interaction that can be attributed to the
apps' algorithmic decision-making. We enriched this data with users' coping and
support strategies through a follow-up online survey (N=286). In particular, we
found problems and strategies related to content, algorithm, user choice, and
feedback. We discuss corresponding implications for designing user support,
highlighting the importance of user control and explanations of output, rather
than processes.

30
The categories of this paper are: q-alg
34
The categories of this paper are: chem-ph
14
The categories of this paper are: math-ph
37
The categories of this paper are: supr-con
10
The categories of this paper are: q-bio
17
The categories of this paper are: q-fin
6
The categories of this paper are: astro-ph
29
The categories of this paper are: funct-an
7
The categories of this paper are: hep-th
26
The categories of this paper are: bayes-an
16
The categories of this paper are: stat
19
The categories of this paper are: eess
5
The categories of this paper are: gr-qc
35
The categories of this paper are: mtrl-th
13
The categories of this paper are: quant-ph
2
The categories of this paper are: math