Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Twitter sentiment analysis on online food services based on elephant herd optimization with hybrid deep learning technique Subject The topic of the resource Deep learning; Elephant herd optimization; Online food service; Pseudoinverse learning autoencoder; Swiggy; Twitter sentiment analysis; Zomato Description An account of the resource Twitter is a social media stage, making it a valuable resource for learning about peoples opinions, feelings, and thoughts. For this reason, experts came up with methods to analyse the tone of tweets and determine whether they were favourable or negative. This article aims to assist businesses, and especially app-based meal delivery businesses, in conducting competitive research on social broadcasting and transforming social broadcasting data into data production for decision-makers. In this analysis, we compared Swiggy, Zomato, and UberEats. Customers tweets about all these brands are obtained using R-Studio, and a deep learning-based sentiment examination approach is functional on the retrieved tweets. The pseudo-inverse learning autoencoder is able to provide feature extraction in the form of an analytic solution after pre-processing, without resorting to many iterations. In this research, we suggest framework for combining the Convolutional Neural Network (CNN) and Bi-directional Long Short Term Memory (Bi-LSTM) models. ConvBiLSTM is used, which is a word embedding model that uses numerical values to represent tweets. The CNN layer takes the feature implanting as input and outputs lower features. In this instance, elephant herd optimization is used to fine-tune the Bi-LSTM weights. Among the three firms, the results indicate that Zomato got the most positive feedback (29%), followed by Swiggy (26%), and UberEats (25%). Zomato also had fewer bad reviews than Swiggy and UberEats, with only 11% of users having a poor experience. In addition, tweets were evaluated for unfavourable views against all three meal delivery services, and suggestions for improvement were offered. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Creator An entity primarily responsible for making the resource Vatambeti R.; Mantena S.V.; Kiran K.V.D.; Manohar M.; Manjunath C. Source A related resource from which the described resource is derived Cluster Computing, Vol-27, No. 1, pp. 655-671. Publisher An entity responsible for making the resource available Springer Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/s10586-023-03970-7" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s10586-023-03970-7</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147314813&amp;doi=10.1007%2Fs10586-023-03970-7&amp;partnerID=40&amp;md5=7f7c62d98b6fc3a7c357514ebaab4f6c" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147314813&amp;doi=10.1007%2fs10586-023-03970-7&amp;partnerID=40&amp;md5=7f7c62d98b6fc3a7c357514ebaab4f6c</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 13867857 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Vatambeti R., School of Computer Science and Engineering, VIT-AP University, Vijayawada, India; Mantena S.V., Department of Computer Science and Engineering, SRKR Engineering College, Bhimavaram, 534204, India; Kiran K.V.D., Department of CSE, Koneru Lakshmaiah Education Foundation, AP, Vaddeswaram, India; Manohar M., Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, India; Manjunath C., Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, India