Year: 2024
Type: article
Abstract: Recently, more and more companies are using machine learning platforms offered by cloud service providers to build sentiment analysis models that can then be used to analyze public opinions via social media. This paper aims to conduct a comparative analysis of two of the most popular cloud computing platforms, namely Amazon Web Services (AWS) and Microsoft Azure, in terms of their sentiment detection services through the complex analysis of multiple texts. The comparative analysis was carried out by implementing an application that integrates both the sentiment analysis (SA) solutions provided by Amazon Web Services and those offered by Microsoft Azure. To evaluate the services offered by the two platforms, different evaluation metrics were analyzed and compared, such as accuracy, precision, recall, and other relevant characteristics. Also, the paper examines the costs and limitations of the two platforms, Amazon Comprehend and Azure AI Language Text, when they are used to implement solutions for analyzing the sentiments of product reviews. The results obtained highlighted the advantages and disadvantages between the two platforms from several perspectives, such as performance, the quality of the answers provided, or their accuracy. All these aspects help to obtain a clear picture of the advantages and limitations of each service offered by the two cloud platforms.
Source: Big Data and Cognitive Computing
DOI: 10.3390/bdcc8120166
Authors: Sergiu C. Ivan, Robert Ş. Győrödi, Cornelia A. Győrödi
Institution: University of Oradea
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,046
OpenAlex ID: W4404594937