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With the exponential growth of online marketplaces and user-generated contenttherein, aspect-based sentiment analysis has become more important than ever.In this work, we critically review a representative sample of the modelspublished during the past six years through the lens of a practitioner, with aneye towards deployment in production. First, our rigorous empirical evaluationreveals poor reproducibility: an average 4-5% drop in test accuracy across thesample. Second, to further bolster our confidence in empirical evaluation, wereport experiments on two challenging data slices, and observe a consistent12-55% drop in accuracy. Third, we study the possibility of transfer acrossdomains and observe that as little as 10-25% of the domain-specific trainingdataset, when used in conjunction with datasets from other domains within thesame locale, largely closes the gap between complete cross-domain and completein-domain predictive performance. Lastly, we open-source two large-scaleannotated review corpora from a large e-commerce portal in India in order toaid the study of replicability and transfer, with the hope that it will fuelfurther growth of the field.

Reproducibility, Replicability and Beyond: Assessing Production Readiness of Aspect Based Sentiment Analysis in the Wild