SA-Q: Observing, Evaluating, and Enhancing the Quality of the Results of Sentiment Analysis Tools
Summary: SA-Q assesses intra- and inter-tool inconsistencies in sentiment-analysis outputs and demonstrates resolution with advanced methods. It recommends dataset-aware tool choices via truth-inference ideas, enabling scalable quality evaluation for NLP. (summarized by gpt-5-nano on Feb 09 2026)
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,937 | Truth Inference in Crowdsourcing: Is the Problem Solved? | 2017 | VLDB | 7.853108e-05 |
| 11,538 | Quality of Sentiment Analysis Tools: The Reasons of Inconsistency | 2021 | VLDB | 4.1945683e-05 |
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