Yashika Sharma

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

E-mail: yashika.1923it1172@kiet.edu


Research Interests: Information Technology Management, Computer Science & Information Technology


Yashika Sharma is currently pursuing her B. Tech degree in information technology from the KIET group of institutions, Murad Nagar, Ghaziabad will be graduating in 2023. She has completed her schooling from R L P K D Vidya mandir school with 79.5%. She has done two internships at IBM and Two Waits’ Technologies in which she made two projects related to web development and learned skills in HTML, CSS, JS and C++. She achieved global rank 2514 in Google Hash code 2022 and has 3 stars at leetcode and 4 stars at code chef-like coding platform. I participated in KICCS-D-HACK 21.0 and acquired a Rank of 4 in the poetry competition.

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: https://doi.org/10.5815/ijem.2023.05.02, 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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