Home
World Journal of Advanced Research and Reviews
International Journal with High Impact Factor for fast publication of Research and Review articles

Main navigation

  • Home
    • Journal Information
    • Editorial Board Members
    • Reviewer Panel
    • Abstracting and Indexing
    • Journal Policies
    • Our CrossMark Policy
    • Publication Ethics
    • Issue in Progress
    • Current Issue
    • Past Issues
    • Instructions for Authors
    • Article processing fee
    • Track Manuscript Status
    • Get Publication Certificate
    • Join Editorial Board
    • Join Reviewer Panel
  • Contact us
  • Downloads

eISSN: 2581-9615 || CODEN: WJARAI || Impact Factor 8.2 ||  CrossRef DOI

Research and review articles are invited for publication in March 2026 (Volume 29, Issue 3) Submit manuscript

Sentiment analysis using Hierarchical Multimodal Fusion (HMF)

Breadcrumb

  • Home
  • Sentiment analysis using Hierarchical Multimodal Fusion (HMF)

Bishwo Prakash Pokharel * and Roshan Koju

Faculty of Science, Health and Technology, Nepal Open University, Bagmati, Nepal.
 
Research Article
World Journal of Advanced Research and Reviews, 2022, 14(03), 296-303
Article DOI: 10.30574/wjarr.2022.14.3.0549
DOI url: https://doi.org/10.30574/wjarr.2022.14.3.0549
 
Received on 08 May 2022; revised on 12 June 2022; accepted on 14 June 2022
 
The rapid rise of platforms like YouTube and Facebook is due to the spread of tablets, smartphones, and other electronic devices. Massive volumes of data are collected every second on such a platform, demanding large-scale data processing. Because these data come in a variety of modalities, including text, audio, and video, sentiment categorization in various modalities and emotional computing are the most researched fields in today's scenario. Companies are striving to make use of this information by developing automated systems for a variety of purposes, such as automated customer feedback collection from user assessments, where the underlying challenge is to mine user sentiment connected to a specific product or service. The use of efficient and effective sentiment analysis tools is required to solve such a complex problem with such a big volume of data. The sentiment analysis of videos is investigated in this study, with data available in three modalities: audio, video, and text. In today's world, modality fusion is a major problem. This study introduces a novel approach to speaker-independent fusion: utilizing deep learning to fuse in a hierarchical fashion. The work tried to obtain improvement over simple concatenation-based fusion.
 
Multi-modal; Bimodal; Sentiment analysis; Hierarchical fusion; Emotion
 
https://wjarr.com/sites/default/files/fulltext_pdf/WJARR-2022-0549.pdf

Preview Article PDF

Bishwo Prakash Pokharel and Roshan Koju. Sentiment analysis using Hierarchical Multimodal Fusion (HMF). World Journal of Advanced Research and Reviews, 2022, 14(3), 296-303. Article DOI: https://doi.org/10.30574/wjarr.2022.14.3.0549

Copyright © Author(s). All rights reserved. This article is published under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution, and reproduction in any medium or format, as long as appropriate credit is given to the original author(s) and source, a link to the license is provided, and any changes made are indicated.

All statements, opinions, and data contained in this publication are solely those of the individual author(s) and contributor(s). The journal, editors, reviewers, and publisher disclaim any responsibility or liability for the content, including accuracy, completeness, or any consequences arising from its use.

Get Certificates

Get Publication Certificate

Download LoA

Check Corssref DOI details

Issue details

Issue Cover Page

Editorial Board

Table of content

Copyright © 2026 World Journal of Advanced Research and Reviews - All rights reserved

Developed & Designed by VS Infosolution