Neural networks with emotion associations, topic modeling and supervised term weighting for sentiment analysis
Článekpeer-reviewedaccepted version (postprint)Datum publikování
2021
Vedoucí práce
Oponent
Název časopisu
Název svazku
Vydavatel
World Scientific Publishing Co.
Abstrakt
Automated sentiment analysis is becoming increasingly recognized due to the growing importance of social media and e-commerce platform review websites. Deep neural networks outperform traditional lexicon-based and machine learning methods by effectively exploiting contextual word embeddings to generate dense document representation. However, this representation model is not fully adequate to capture topical semantics and the sentiment polarity of words. To overcome these problems, a novel sentiment analysis model is proposed that utilizes richer document representations of word-emotion associations and topic models, which is the main computational novelty of this study. The sentiment analysis model integrates word embeddings with lexicon-based sentiment and emotion indicators, including negations and emoticons, and to further improve its performance, a topic modeling component is utilized together with a bag-of-words model based on a supervised term weighting scheme. The effectiveness of the proposed model is evaluated using large datasets of Amazon product reviews and hotel reviews. Experimental results prove that the proposed document representation is valid for the sentiment analysis of product and hotel reviews, irrespective of their class imbalance. The results also show that the proposed model improves on existing machine learning methods.
Rozsah stran
p. 2150013
ISSN
0129-0657
Trvalý odkaz na tento záznam
Projekt
GA19-15498S/Modelování emocí ve verbální a neverbální manažerské komunikaci pro predikci podnikových finančních rizik
Zdrojový dokument
International Journal of Neural Systems, volume 31, issue: 10
Vydavatelská verze
https://www.worldscientific.com/doi/abs/10.1142/S0129065721500131
Přístup k e-verzi
open access (green)
Název akce
ISBN
Studijní obor
Studijní program
Signatura tištěné verze
Umístění tištěné verze
Přístup k tištěné verzi
Klíčová slova
sentiment analysis, word embedding, term weighting, topic model, deep neural network
Endorsement
Review
item.page.supplemented
item.page.referenced
Creative Commons license
Except where otherwised noted, this item's license is described as open access (green)