The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
The Role of Multi-Modal Sentiment Analysis in Optimizing Leadership Communication
|
|
Author(s): Ashish Khosla (Shoolini University, India)and Gaurav Gupta (Shoolini University, India)
Copyright: 2025
Pages: 32
Source title:
Ethical Dimensions of AI Development
Source Author(s)/Editor(s): Pronaya Bhattacharya (Amity University, Kolkata, India), Ahdi Hassan (Global Institute for Research Education and Scholarship, The Netherlands), Haipeng Liu (Centre for Intelligent Healthcare, Coventry University, UK)and Bharat Bhushan (Sharda University, India)
DOI: 10.4018/979-8-3693-4147-6.ch017
Purchase
|
Abstract
Leadership involves more than words, and good communication can help achieve any goal. Effectiveness depends. To understand, multi-modal sentiment analysis uses multiple data sources. This strategy provides insights to improve machine learning modelling. This study optimises leadership communication via visual, auditory, and spoken sentiment analysis. Visual analysis examines facial expressions and body language; vocal analysis studies speech, emotion tones, linguistic cues, and fluency. Machine learning and natural language processing boost leadership communication emotional awareness in three key areas with multi-modal sentiment analysis. Leadership training using multi-modal sentiment analysis and real-time feedback improves empathy and communication. Highlighting multi-modal leadership communication highlighted this growing technology and technique's data integration, interpretability, and scalability problems.
Related Content
|
Sahar Yousif Mohammed, Maad M. Mijwil, Duaa Hikmat Abbas, Kamal Kant Hiran, Ali Guma, Indu Bala, Aseed Yaseen Rashid Al-Jubori.
© 2026.
16 pages.
|
|
Kashvi Chaturvedi, Yadnyesh Khapekar, Sunil Sankathala, Aditya Shrivastav, Atharva Haresh Saraf, Susanta Das.
© 2026.
24 pages.
|
|
Snehal Rahul Rathi, Aditi Meshram, Ritik Narote, Shilpa Prashant Kalantri.
© 2026.
24 pages.
|
|
Rituraj Jain, Ashish Sharna, Venkateswararao Pulipati, Nausheen Khilji, Rakesh Saxena.
© 2026.
30 pages.
|
|
Fredrick Kayusi, Linety Juma, Michael Keari Omwenga, Petros Keari Chavula, Maad M. Mijwil, Kamal Kant Hiran, Bismarck Agura Kayus, Manish Tiwari.
© 2026.
32 pages.
|
|
Neha Yadav, Mayank Singh, Vipin Tyagi.
© 2026.
24 pages.
|
|
Manish Mittal, Manish Tiwari, Ruchi Doshi, Kamal Kant Hiran.
© 2026.
24 pages.
|
|
|