Loading article...
Loading article...
Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM33351
Volume:
8 |
5 |
May 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Social media platforms have become indispensable channels for communication and interaction, offering a wealth of data that can provide valuable insights into public sentiments. However, analyzing sentiment on these platforms poses significant challenges due to the diverse and unstructured nature of user-generated content. Traditional Natural Language Processing (NLP) techniques struggle to accurately classify sentiments expressed through text, images, emoticons, and multimedia elements. Moreover, the informal and nuanced language used in Electronic Word of Mouth (eWOM) further complicates sentiment analysis. In response, this paper explores the role of Artificial Intelligence (AI) in improving sentiment analysis on social media. By leveraging Machine Learning (ML) algorithms trained on large datasets, AI can enhance the accuracy and efficiency of sentiment classification, providing decision-makers with actionable insights into the sentiment landscape of social media.
KEYWORDS
Publication Date
12/31/45427
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
Documents
Article Views
0
Total views since publication
PDF Downloads
3
Total downloads since publication
Geographic Reach
5
Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.
Plagiarism Screening
This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.
Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
Related research in the same subject area
Loading similar articles...