Smart Decisions with Opinion Mining

Dinesh M and Dr. R. Priya
Additional contact information
Dinesh M: Vels Unversity, India
Dr. R. Priya: Professor, Department of Computer Applications, VISTAS

International Journal of Latest Technology in Engineering, Management & Applied Science, 2025, vol. 14, issue 4, 466-471

Abstract: The runaway growth of web technology has resulted in an unprecedented volume of data being produced and published on the web each day. Social networking sites such as Twitter and Facebook have turned into indispensable zones for individuals to share thoughts, experiences, and opinions around the world. Sentiment analysis which involves the extraction and analysis of opinion from text, is central to gauging public feeling, monitoring trends, business strategy, and customer satisfaction with regards to unstructured and heterogeneous nature of Twitter data, most research has been conducted on how to use sentiment analysis methods to classify opinion as positive, negative, or neutral. In this paper, sentiment analysis of social media data is investigated based on a Twitter dataset, utilizing machine learning methods such as Long Short-Term Memory (LSTM) networks for precise sentiment classification.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.ijltemas.in/DigitalLibrary/Vol.14Issue4/466-471.pdf (application/pdf)
https://www.ijltemas.in/papers/volume-14-issue-4/466-471.html (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bjb:journl:v:14:y:2025:i:4:p:466-471

Access Statistics for this article

International Journal of Latest Technology in Engineering, Management & Applied Science is currently edited by Dr. Pawan Verma

More articles in International Journal of Latest Technology in Engineering, Management & Applied Science from International Journal of Latest Technology in Engineering, Management & Applied Science (IJLTEMAS)
Bibliographic data for series maintained by Dr. Pawan Verma ().