A Comparative Evaluation of Classification Algorithms for Sentiment Analysis Using Word Embeddings

2020 ◽  
pp. 1-11
Author(s):  
Hanane Elfaik ◽  
El Habib Nfaoui
Keyword(s):  
Sentiment Analysis ◽  
Comparative Evaluation ◽  
Classification Algorithms ◽  
Word Embeddings

Learning emotional word embeddings for sentiment analysis

2021 ◽  
pp. 1-13
Author(s):  
Qingtian Zeng ◽  
Xishi Zhao ◽  
Xiaohui Hu ◽  
Hua Duan ◽  
Zhongying Zhao ◽  
...  
Keyword(s):  
Sentiment Analysis ◽  
Language Processing ◽  
State Of The Art ◽  
Research Problem ◽  
Emotional Word ◽  
Classification Model ◽  
Data Sets ◽  
Word Embeddings ◽  
Real World Data ◽  
Text Documents

Word embeddings have been successfully applied in many natural language processing tasks due to its their effectiveness. However, the state-of-the-art algorithms for learning word representations from large amounts of text documents ignore emotional information, which is a significant research problem that must be addressed. To solve the above problem, we propose an emotional word embedding (EWE) model for sentiment analysis in this paper. This method first applies pre-trained word vectors to represent document features using two different linear weighting methods. Then, the resulting document vectors are input to a classification model and used to train a text sentiment classifier, which is based on a neural network. In this way, the emotional polarity of the text is propagated into the word vectors. The experimental results on three kinds of real-world data sets demonstrate that the proposed EWE model achieves superior performances on text sentiment prediction, text similarity calculation, and word emotional expression tasks compared to other state-of-the-art models.

scholarly journals More than Bags of Words: Sentiment Analysis with Word Embeddings

2018 ◽  
Vol 12 (2-3) ◽  
pp. 140-157 ◽  
Author(s):  
Elena Rudkowsky ◽  
Martin Haselmayer ◽  
Matthias Wastian ◽  
Marcelo Jenny ◽  
Štefan Emrich ◽  
...  
Keyword(s):  
Sentiment Analysis ◽  
Word Embeddings

scholarly journals Mucinous Adenocarcinoma Involving the Ovary: Comparative Evaluation of the Classification Algorithms using Tumor Size and Laterality

2010 ◽  
Vol 25 (2) ◽  
pp. 220 ◽  
Author(s):  
Eun Sun Jung ◽  
Jeong Hoon Bae ◽  
Ahwon Lee ◽  
Yeong Jin Choi ◽  
Jong-Sup Park ◽  
...  
Keyword(s):  
Tumor Size ◽  
Mucinous Adenocarcinoma ◽  
Comparative Evaluation ◽  
Classification Algorithms
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