Sentiment Analysis and Affective computing in Multimedia Data on Social Network

## Introduction

In the age of multimedia and social network, there is a rapid growth in user generated data, which needs to be analyzed, processed to understand the user subjective perception. Sentiment analysis is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language. The Affective Computing is the study and development of systems and devices that can recognize, interpret, process, and simulate human affects. It is a new ways of bringing together Emotion AI and other affective technologies in order to make people's lives better. As the rapid growth of user-generated data from social networks, wikis and social tagging systems, it is necessary to understand the high-level semantics and user subjective perceptions from such a large volume of data. Emotions or sentiments are one of the most important aspects as the user-generated data are always with emotional loads of their creators. Along with the development of the computational techniques for sentiment analysis and opinion mining, the increasing psychological and cognitive models/theories are exploited for modeling sentiments and emotions by incorporating with social computing techniques such as social network and personalization, mining user reviews, user profiling in social network and so on. Connecting affective/sentimental models and social computing techniques not only can facilitate the understanding big data in at semantic-levels but also improve the performance of various social computing applications in the big data era. It combines affective/sentimental models with social computing as a promising direction and offers opportunities for developing novel algorithms, methods and tools.

This special issue will be a platform to researchers to provide the opportunity to address the recent trends in “Sentiment Analysis and Affective computing in Multimedia Data on Social Network”. This issue will also promote significant research contributions by scholars and scientist worldwide included specific topics. This will be also a good reference to the professional in this area of research, target to present, endorse and discuss current research.

## Recommended topics (but not limited to)

Authors are invited for original contributions on, but not limited to, the themes and topics in the following areas of research:

• Aspect-based sentiment analysis,
• Personalized sentiment analysis,
• Context-based sentiment analysis,
• Multi-model sentiment analysis,
• Multilingual aspect of sentiment analysis,
• Real-time sentiment analysis and its research perspective,
• Computing resources for sentiment analysis or Affective Computing,
• Effective sentiment analysis with limited computing resources,
• Affective Computing with limited resources,
• Sarcasm detection,
• Fake review detection,
• Fake news classification,
• Vocal language context identification,
• Authenticity of viral message/video/clip detection,
• Sentiment analysis tools and its application,
• Application perspective of Sentiment analysis,
• Sentiment analysis and finance,
• Sentiment analysis and healthcare,
• Sentiment analysis and digital marketing,
• Sentiment analysis and direct selling,
• Recommendation Systems,
• Context-aware recommendation systems,
• Personalized recommendation systems,
• Dynamic recommendation systems,
• Opinion Mining, and

Many more…

## Important dates

Submission deadline: 31 July, 2023

Authors notification: 15 September, 2023

Final version submission: 15 October, 2023

## Submission guidelines

Original and unpublished works on any of the topics aforementioned or related are welcome. The SCPE journal has a rigorous peer-reviewing process and papers will be reviewed by at least two referees. All submitted papers must be formatted according to the journal's instructions, which can be found here.

During submission please select a Special Issue that you want to submit to and provide this information in the Comments for the Editor field.

## Guest Editors

Dr. Rajni Mohana, Associate Professor, CS/IT Department, Jaypee University of Information and Technology, Solan, H.P., India

Dr. Anand Nayyar, Lecturer, Researcher and Scientist, Graduate School, Duy Tan University, 254 Nguyen Van Ling Street, Duy Tan University, Da Nang 550000, Viet Nam

Dr Pradeep Kumar, Associate Professor, Discipline of Electrical, Electronic and Computer Engineering, University of KwaZulu-Natal, South Africa

Dr Aman Sharma, Assistant Professor (SG), CS/IT Department, Jaypee University of Information and Technology, Solan, H.P., India