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cs.HC updates on arXiv.org

Quantitative Movement Testing: Measuring Patient Movements from a Single Smartphone Video Vision-Language Models Suppress Female Representations Under Ambiguous Input The New Social Image: How AI Competency and AI Proactivity Influence Self- and Peer-Perceptions in the Workplace TUX: Measuring Human--AI Tacit Understanding LLUMI: Improving LLM Writing Assistance for Mental Health Support with Online Community Feedback VideoFDB: Evaluating Full-Duplex Vision-Speech Capabilities in Conversational Agents Label Over Logic? How Source Cues Bias Human Fallacy Judgments More Than LLMs Inform, Coach, Relate, Listen: Auditing LLM Caregiving Support Roles How Coding Agents Fail Their Users: A Large-Scale Analysis of Developer-Agent Misalignment in 20,574 Real-World Sessions MetaRanker: Human-in-the-loop Active Ranking for Metalens Image Quality Analyzing Persona Effects in Generated Explanations from Multimodal LLM Agents in Urban Perception First head-to-head comparison of agentic AI applied to the analysis of simulated data of the Einstein Telescope Granuscore: A Reference-Free Measure of Granularity for Text Analysis and Question Answering The Timing Dependencies of Trust: Speed, Accuracy, and cBCI Neuro-Decoupling in Human-AI Teams Bayesian Distributional Models of Executive Functioning Visual Matters: Connecting Aesthetic Appeal and Production Quality of Photos, Infographics and Data Visualizations to Credibility of Social Media Posts Data-driven Head Motion Generation through Natural Gaze-Head Coordination Agreement Metrics for LLM-as-Judge Evaluation: What to Report and Why Perceptually Lossless Tactile Texture Synthesis with Compact Spectral Envelope Models MambaGaze: Bidirectional Mamba with Explicit Missing Data Modeling for Cognitive Load Assessment from Eye-Gaze Tracking Data CogAdapt: Transferring Clinical ECG Foundation Models to Wearable Cognitive Load Assessment via Lead Adaptation Augmented Analytics and Decision Quality: The Role of Trust among Non-Technical BI Users Faster Completion, Less Learning: Generative AI Reduced Study Time on Math Problems and the Knowledge They Build PaintCopilot: Modeling Painting as Autonomous Artistic Continuation Personality Engineering with AI Agents: A New Methodology for Negotiation Research PULSE: Agentic Investigation with Passive Sensing for Proactive Intervention in Cancer Survivorship Access Timing as Scaffolding: A Reinforcement Learning Approach to GenAI in Education Conversations in Space: Structuring Non-Linear LLM Interactions on a Canvas MAPLE: Self-Supervised Learning-Enhanced Nonlinear Dimensionality Reduction for Visual Analysis nASR: An End-to-End Trainable Neural Layer for Channel-Level EEG Artifact Subspace Reconstruction in Real-Time BCI
Color and Sentiment: A Study of Emotion-Based Color Palet...
Maksat Shagyrov, Pakizar Shamoi · 2024-07-23 · via cs.HC updates on arXiv.org

It's widely recognized that the colors used in branding significantly impact how a brand is perceived. This research explores the influence of color in logos on consumer perception and emotional response. We investigate the associations between color usage and emotional responses in food and beverage marketing. Using a dataset of 644 companies, we analyzed the dominant colors in brand logos using k-means clustering to develop distinct color palettes. Concurrently, we extracted customer sentiments and emotions from Google Maps reviews of these companies (n=30,069), categorizing them into five primary emotions: Happiness, Anger, Sadness, Fear, and Surprise. These emotional responses were further categorized into four intensity levels: Low, Medium, Strong, and Very Strong, using a fuzzy sets approach. Our methodology involved correlating specific color palettes with the predominant emotional reactions associated with each brand. By merging the color palettes of companies that elicited similar emotional responses, we identified unique color palettes corresponding to each emotional category. Our findings suggest that among the food companies analyzed, the dominant emotion was Happiness, with no instances of Anger. The colors red and gray were prevalent across all emotional categories, indicating their importance in branding. Specific color-emotion correlations confirmed by our research include associations of yellow with Happiness, blue with Sadness, and bright colors with Surprise. This study highlights the critical role of color in shaping consumer attitudes. The study findings have practical implications for brand designers in the food industry.