Shivam Yadav

Work place: KIET Group of Institutions, Uttar Pradesh, Delhi NCR, Ghaziabad, India



Research Interests: Web Technologies, Data Structures and Algorithms


Shivam Yadav is currently pursuing his B. Tech degree in Information Technology from the KIET group of institutions, Murad Nagar, Ghaziabad, and will be graduating in 2023. He has completed his schooling from KV Uttarlai Barmer with 89.8%. His area of interest is frontend web development, artificial intelligence, machine learning and Deep learning. He has made the project on frontend web development in which Kiet discussion form, and bank management system using technology stack c++, HTML, CSS, react JS and git. His skills are Data structure and algorithms, web development, CPP and Java. He also worked on a research paper COVID disease detection system using prolog system which is published in Joscex.

Author Articles
An Automated Model for Sentimental Analysis Using Long Short-Term Memory-based Deep Learning Model

By Shashank Mishra Mukul Aggarwal Shivam Yadav Yashika Sharma

DOI:, Pub. Date: 8 Oct. 2023

A post, review, or news article's emotional tone can be automatically ascertained using sentiment analysis, a natural language processing approach. Sorting the text into positive, negative, or neutral categories is the aim of sentiment analysis. Many methods, including rule-based systems and machine learning algorithms, can be used to analyse sentiment, or deep learning models. These techniques typically involve analyzing various features of the text, such as word choice, sentence structure, and context, to identify the overall sentiment. Here long short-term memory-based deep learning is applied in this research for the model development purpose. Deeply interconnected neural networks are used in this method. Sentiment analysis can be used in many different applications, such as market research, brand reputation management, customer feedback analysis, and social media monitoring. It shows the use of sentiment analysis in a variety of fields and increases the need of technology to perform it on the existing machines.

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