Automated ADR Analysis from Twitter Data Using N-Gram-Based Feature Extraction Methods and Supervised Learning Classification
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-1745-7_31
Reference19 articles.
1. Min Z (2019) Drugs reviews sentiment analysis using weakly supervised model. In: 2019 IEEE international conference on artificial intelligence and computer applications (ICAICA), pp 332–336. https://doi.org/10.1109/ICAICA.2019.8873466
2. Meškele D, Frasincar F (May 2020) ALDONAr: a hybrid solution for sentence-level aspect-based sentiment analysis using a lexicalized domain ontology and a regularized neural attention model. Inf Process Manag 57(3). Art. no. 102211
3. El Rahman SA, AlOtaibi FA, AlShehri WA (2019) Sentiment analysis of Twitter data. In: 2019 international conference on computer and information sciences (ICCIS). IEEE, pp 1–4
4. Wagh R, Punde P (2018) Survey on sentiment analysis using twitter dataset. In: 2018 second international conference on electronics, communication and aerospace technology (ICECA). IEEE, pp 208–211
5. Gautam G, Yadav D (2014) Sentiment analysis of twitter data using machine learning approaches and semantic analysis
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