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arXiv · 2004.00300

Can We Use SE-specific Sentiment Analysis Tools in a Cross-Platform Setting?

Nicole Novielli·Fabio Calefato·Davide Dongiovanni·Daniela Girardi·Filippo Lanubile
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Abstract

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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Nicole Novielli, Fabio Calefato, Davide Dongiovanni, Daniela Girardi, Filippo Lanubile. 2020-04-01. Can We Use SE-specific Sentiment Analysis Tools in a Cross-Platform Setting?. https://doi.org/10.1145/3379597.3387446

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