Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Can We Use SE-specific Sentiment Analysis Tools in a Cross-Platform
  Setting?   In this paper, we address the problem of using sentiment analysis tools
'off-the-shelf,' that is when a gold standard is not available for retraining.
We evaluate the performance of four SE-specific tools in a cross-platform
setting, i.e., on a test set collected from data sources different from the one
used for training. We find that (i) the lexicon-based tools outperform the
supervised approaches retrained in a cross-platform setting and (ii) retraining
can be beneficial in within-platform settings in the presence of robust gold
standard datasets, even using a minimal training set. Based on our empirical
findings, we derive guidelines for reliable use of sentiment analysis tools in
software engineering.

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The categories of this paper are: math-ph
13
The categories of this paper are: quant-ph
21
The categories of this paper are: adap-org
34
The categories of this paper are: chem-ph
20
The categories of this paper are: acc-phys
35
The categories of this paper are: mtrl-th
37
The categories of this paper are: supr-con
10
The categories of this paper are: q-bio
2
The categories of this paper are: math
11
The categories of this paper are: hep-lat
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The categories of this paper are: eess
12
The categories of this paper are: nucl-th
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The categories of this paper are: chao-dyn
9
The categories of this paper are: nlin
0
The categories of this paper are: hep-ph
28
The categories of this paper are: alg-geom