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Emotion-Driven Interior Design Using Sentiment Analysis from Social Media
- 1 Manchester school of architecture, The University of Manchester, MA, UK
- 2 Manchester school of architecture, The University of Manchester, MA, UK
* Author to whom correspondence should be addressed.
Abstract
The gradual development and expansion of online social media provides a stage for people to share their personal views and opinions. Many experts and scholars have collected and analyzed these emotions, created numerous emotional models and data sets, which are widely used in various fields including architectural interior design. Through sentiment analysis techniques, it has become an important branch in interior design to investigate how to optimise user’s emotional experience, such as comfort, sense of belonging and well-being. This paper selects GoEmotions as the dataset for sentiment classification and analysis of text, which is currently the largest manually annotated dataset. By analyzing the comments on Instagram posts related to interior design, the study investigates the impact of residential interior space design on people's emotions, and then trains a Low-Rank Adaptation (LoRA) model that can generate interior spaces with certain emotional feelings.
Keywords
Interior design, Deep learning, Emotion recognition, Low-Rank Adaptation
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Cite this article
Chu,L.;Zhou,K. (2025). Emotion-Driven Interior Design Using Sentiment Analysis from Social Media. Applied and Computational Engineering,108,193-201.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of the 5th International Conference on Signal Processing and Machine Learning
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