Journal

Volume 26, Issue 3 (September 30, 2025)

3 articles

• A Systematic Literature Review on Enhancing Sarcasm Detection in Online Reviews through Emotional Transition Analysis and Contextual Embedding Techniques
  by Stephen Olamilekan Adedigba, Mohamad Hardyman Barawi, Ebuka Ibeke and Norazuna Norahim
  J. CS. 2025, 26(3), 227-269;
  Abstract Analysing online reviews is crucial for understanding user sentiments, yet sarcasm often hinders accurate sentiment evaluation. In this systematic literature review (SLR), we addressed the challenging task of sarcasm detection in online reviews, focusing on two key aspects: emotional transitions wit... [Read more].
  Abstract Analysing online reviews is crucial for understanding user sentiments, yet sarcasm often hinders accurate sentiment evaluation. In this systematic literature review (SLR), we addressed the challenging task of sarcasm detection in online reviews, focusing on two key aspects: emotional transitions within reviews and the capabilities of contextual embedding techniques. Due to the context-sensitive and multifaceted nature of sarcasm, most traditional natural language processing (NLP) systems struggle to detect sentiment accurately. To identify sentiment shifts indicative of sarcasm, this systematic literature review (SLR) examines existing literature on emotion transitions within review texts. This review aims to illuminate the linguistic cues associated with sarcastic sentiment reversals. In order to identify these cues more effectively, we further explore the application of advanced contextual embedding models, such as BERT and ELMo, for their ability to detect and analyse sarcastic expressions. By synthesising these findings, we offer a comprehensive overview of current approaches to sarcasm detection in sentiment analysis. Additionally, this review critically analyses the limitations of existing methods and proposes potential avenues for improvement. We aim to explicate the effectiveness of sarcasm detection in sentiment analysis applications used on social media platforms like X (Twitter), Reddit, Facebook, and WeChat. In brief, this review provides valuable insights into the field of sentiment analysis and emotion detection, paving the way for the development of NLP systems with a refined ability to discern intricate emotional and contextual embedding in online reviews. [Collapse]
• Facial Color and Semantic Priming in the Perception of Emotional Expressions
  by Chungyu Park & Jiyoun Choi
  J. CS. 2025, 26(3), 271-288;
  Abstract Facial expressions are primary cues for emotion perception, yet their interpretation is influenced by contextual factors. Color is one such factor, carrying affective meanings that may affect how emotional expressions are recognized. The present study examined how red and yellow facial colors affect... [Read more].
  Abstract Facial expressions are primary cues for emotion perception, yet their interpretation is influenced by contextual factors. Color is one such factor, carrying affective meanings that may affect how emotional expressions are recognized. The present study examined how red and yellow facial colors affect the recognition of anger and happiness expressions in Korean participants, and whether these effects are modulated by semantic priming. Participants first completed a Stroop task designed either to strengthen color–emotion associations (congruent priming condition) or to present colors in a non-associative manner (incongruent priming condition). They then judged facial expressions overlaid with red or yellow hues. Results showed that red facilitated recognition of angry faces, whereas yellow facilitated recognition of happy faces, with these effects being robust under the semantic priming condition. Reaction time analyses further revealed a facilitative effect of yellow on happy face recognition, while the facilitation of red on anger was less consistent. These findings suggest that color acts not only as a perceptual cue but also as a conceptually grounded signal that interacts with higher-order semantic processes in shaping emotional face perception. [Collapse]
• A Corpus-Based Case Study of Human Insight into Concepts and Reality and Its Philosophical Implications: Japanese Jibun ‘Self’ and Shiawase ‘Happiness’
  by Yoko Mizuta
  J. CS. 2025, 26(3), 289-335;
  Abstract This paper aims to explore the dynamic aspect of deepening our understanding of concepts and reality that involves experiences and thought at later stages of our lives along personal and social dimensions. We take a linguistic approach, using corpus data focusing on examples of Japanese hontōno {jib... [Read more].
  Abstract This paper aims to explore the dynamic aspect of deepening our understanding of concepts and reality that involves experiences and thought at later stages of our lives along personal and social dimensions. We take a linguistic approach, using corpus data focusing on examples of Japanese hontōno {jibun/ shiawase} ‘true {self/ happiness}’ and their lexical variants. Insights about the concept and reality of hontōno {jibun/ shiawase} are identified and organized in terms of classification and contrast. Then qualitative and quantitative analyses of the corpus data that are annotated with the identified insights are provided. The analysis demonstrates that the meaning of jibun and shiawase extends beyond lexical and encyclopedic knowledge and reflects the process of seeking and approaching truth with a critical stance toward the world around us (e.g. a common sense of values). Hontōno is fundamentally involved in this process and functions as a contrast marker reflecting human critical thinking. The discussion includes a comparison between the empirical insights about shiawase and Aristotle’s philosophical thought on eudimonia ‘happiness’ as presented in Nicomachean Ethics. The findings suggest that the proposed corpus-based analysis serves as an effective means for obtaining and utilizing empirical data for the exploration of philosophical issues as well as lexical semantics and pragmatics. [Collapse]