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Aspect-Based Sentiment Analysis/Evidence
Method evidence record

Aspect-Based Sentiment Analysis

Aspect-based sentiment analysis (ABSA) is a fine-grained natural-language-processing task that detects sentiment separately for each aspect or feature mentioned in a text — such as a product's quality, price, or service — rather than scoring the document as a whole. It was consolidated as a shared task by Pontiki et al. in SemEval-2014 Task 4.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Aspect-Based Sentiment Analysis (ABSA)
Taxonomic method record · process-pipeline / text-mining
  • Pontiki, M. et al. (2014). SemEval-2014 Task 4: Aspect Based Sentiment Analysis. Proceedings of SemEval 2014, 27-35. · DOI 10.3115/v1/S14-2004
  • Schouten, K. & Frasincar, F. (2016). Survey on Aspect-Level Sentiment Analysis. IEEE Transactions on Knowledge and Data Engineering, 28(3), 813-830. · DOI 10.1109/TKDE.2015.2485209
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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Same method familyNamed Entity Recognitionmachine-suggested · Relational suggestion, not evidence.Same method familySentiment Analysismachine-suggested · Relational suggestion, not evidence.Same method familyText Classificationmachine-suggested · Relational suggestion, not evidence.See alsoTopic Modelingmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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