Aueb.Twitter.Sentiment at SemEval-2016 Task 4: A Weighted Ensemble of SVMs for Twitter Sentiment Analysis

机译：Aueb.Twitter.Sentiment在SemEval-2016上的任务4：用于Twitter情绪分析的SVM的加权集合

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This paper describes the system with which we participated in SemEval-2016 Task 4 (Sentiment Analysis in Twitter) and specifically the Message Polarity Classification subtask. Our system is a weighted ensemble of two systems. The first one is based on a previous sentiment analysis system and uses manually crafted features. The second system of our ensemble uses features based on word embed-dings. Our ensemble was ranked 5th among 34 teams. The source code of our system is publicly available.

机译：本文介绍了我们参与SemEval-2016任务4（Twitter中的情感分析）的系统，尤其是“消息极性分类”子任务。我们的系统是两个系统的加权集合。第一个基于以前的情感分析系统，并使用手工制作的功能。我们集成的第二个系统使用基于单词嵌入的功能。我们的合唱团在34支球队中排名第五。我们系统的源代码是公开可用的。

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《International workshop on semantic evaluation;Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies》|2016年|96-99|共4页
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Stavros Giorgis; Apostolos Rousas; John Pavlopoulos; Prodromos Malakasiotis; Ion Androutsopoulos;
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1. HYBRID MODEL FOR TWITTER DATA SENTIMENT ANALYSIS BASED ON ENSEMBLE OF DICTIONARY BASED CLASSIFIER AND STACKED MACHINE LEARNING CLASSIFIERS-SVM, KNN AND C5.0 [J] . SANGEETA RANI, NASIB SINGH GILL Journal of Theoretical and Applied Information Technology . 2020,第4期

机译：基于字典的分类器和堆叠机学习分类分类的基于词典的Twitter数据情绪分析混合模型 - SVM，KNN和C5.0
2. Performance analysis of sentiments in Twitter dataset using SVM models [J] . Lakshmana Kumar Ramasamy, Seifedine Kadry, Yunyoung Nam, International Journal of Electrical and Computer Engineering . 2021,第3期

机译：使用SVM模型的Twitter DataSet情绪分析
3. Sentiment Analysis on KAI Twitter Post Using Multiclass Support Vector Machine (SVM) [J] . Dhina Nur Fitriana, Yuliant Sibaroni Jurnal RESTI: Rekayasa Sistem dan Teknologi Informasi . 2020,第5期

机译：凯推特柱的情感分析使用多碳支持向量机（SVM）
4. Aueb.Twitter.Sentiment at SemEval-2016 Task 4: A Weighted Ensemble of SVMs for Twitter Sentiment Analysis [C] . Stavros Giorgis, Apostolos Rousas, John Pavlopoulos, International workshop on semantic evaluation . 2016

机译：Aueb.Twitter.centiment在Semeval-2016任务4：Twitter情感分析的SVMS加权集合
5. A New Opinion Review Methodology for Arabic Twitter Sentiment Analysis [D] . Almalki, Abdullah S. 2020

机译：阿拉伯语推特情绪分析的新意见审查方法
6. A Novel Bearing Multi-Fault Diagnosis Approach Based on Weighted Permutation Entropy and an Improved SVM Ensemble Classifier [O] . Shenghan Zhou, Silin Qian, Wenbing Chang, 2018

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7. GTI at SemEval-2016 Task 5: SVM and CRF for Aspect Detection and Unsupervised Aspect-Based Sentiment Analysis [O] . Tamara Àlvarez-López, Jonathan Juncal-Martínez, Milagros Fernández-Gavilanes, 2016

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Aueb.Twitter.Sentiment at SemEval-2016 Task 4: A Weighted Ensemble of SVMs for Twitter Sentiment Analysis

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