A Comparative Analysis of Sentiment Analysis Using RNN-LSTM and Logistic Regression

Title

A Comparative Analysis of Sentiment Analysis Using RNN-LSTM and Logistic Regression

Creator

Goswami M.; Sajwan P.

Description

Social media analytics makes a big difference in the success or failure of an organization. The data gathered from social media can be used to get a hit type product by analyzing the data and getting important information about the need of the people. This can be done by implementing sentiment analysis on the available data and then accessing the feelings of the customers about the product or service and knowing if it is actually being liked by them or not. Tracking data of the customers helps the organization in many ways. This study was done to get familiarized with the concept of data analytics and how social media plays an important role in it. Furthermore, Web scraping of Twitter and YouTube data was done following which a standard dataset was selected to do the other analytics. The field of sentiment analysis was used to get the emotions of the people. Logistic regression and RNN-LSTM models were used to perform the same, and then, the results were compared. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Source

Lecture Notes in Electrical Engineering, Vol-740 LNEE, pp. 165-174.

Date

2021-01-01

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

Descriptive analytics; Logistic regression; Predictive analytics; RNN-LSTM; Sentiment analysis

Coverage

Goswami M., Christ University, Bengaluru, India; Sajwan P., Christ University, Bengaluru, India

Rights

Restricted Access

Relation

ISSN: 18761100; ISBN: 978-981336392-2

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-981-33-6393-9_18

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85105865696&doi=10.1007%2f978-981-33-6393-9_18&partnerID=40&md5=1fb928e0b91baeb3aee5d07ca88fd275