A Deep Learning Approach for Twitter Sentiment Analysis using ULM-SVM DOI

L. Sudha Rani,

S. Zahoor-Ul-Huq,

C. Shoba Bindu

et al.

2022 9th International Conference on Computing for Sustainable Global Development (INDIACom), Journal Year: 2024, Volume and Issue: unknown, P. 1639 - 1643

Published: Feb. 28, 2024

Through Twitter sentiment Analysis, users can easily determine the quality of their products and services. These tools are very useful in identifying monitoring various factors that affect these services products. The classification accuracy is dependent on input features techniques used. Unfortunately, time constraints associated with implementing machine learning prevent many organizations from achieving goals. Deep used applications, such as analysis, to extract information large amounts data. goal this study develop a new method for analyzing uses deep techniques. This combines ULM-SVM. proposed employs analyze sentiment, which seeks identify users' sentiments toward particular based posts. evaluation model across three datasets revealed its exceptional performance, an 98.7% detecting dataset.

Language: Английский

An ocean water current-inspired Geoscience based optimization algorithm DOI
Aishwarya Mishra, Lavika Goel

International Journal of Information Technology, Journal Year: 2024, Volume and Issue: 16(4), P. 2619 - 2633

Published: Jan. 14, 2024

Language: Английский

Citations

6
Performance enhancement of deep neural network using fusional data assimilation and divide-and-conquer approach; case study: earthquake magnitude calculation DOI
Rezvan Esmaeili, Roohollah Kimiaefar, Alireza Hajian

et al.

Neural Computing and Applications, Journal Year: 2024, Volume and Issue: 36(27), P. 16899 - 16910

Published: June 3, 2024

Language: Английский

Citations

1
A Natural Way to Stability: A New Evolutionary Algorithm Based on Ocean Water Currents DOI
Aishwarya Mishra, Lavika Goel

Proceedings in adaptation, learning and optimization, Journal Year: 2024, Volume and Issue: unknown, P. 241 - 256

Published: Jan. 1, 2024

Language: Английский

Citations

1
A Deep Learning Approach for Twitter Sentiment Analysis using ULM-SVM DOI

L. Sudha Rani,

S. Zahoor-Ul-Huq,

C. Shoba Bindu

et al.

2022 9th International Conference on Computing for Sustainable Global Development (INDIACom), Journal Year: 2024, Volume and Issue: unknown, P. 1639 - 1643

Published: Feb. 28, 2024

Through Twitter sentiment Analysis, users can easily determine the quality of their products and services. These tools are very useful in identifying monitoring various factors that affect these services products. The classification accuracy is dependent on input features techniques used. Unfortunately, time constraints associated with implementing machine learning prevent many organizations from achieving goals. Deep used applications, such as analysis, to extract information large amounts data. goal this study develop a new method for analyzing uses deep techniques. This combines ULM-SVM. proposed employs analyze sentiment, which seeks identify users' sentiments toward particular based posts. evaluation model across three datasets revealed its exceptional performance, an 98.7% detecting dataset.

Language: Английский

Citations

0