Asymmetric emoji-word interactions in emotional processing: Evidence from priming and drift diffusion modeling.

Area of Science:

• Cognitive Psychology
• Human-Computer Interaction
• Affective Computing

Background:

• Emojis are increasingly used in digital communication, yet their integration with verbal emotional information is not fully understood.
• Understanding the interplay between emoji and word valence is crucial for interpreting emotional communication in digital contexts.

Purpose of the Study:

• To investigate the interactive effects and cognitive mechanisms of integrating emotional information from emojis and words.
• To examine the bidirectional influences between emotional words and emojis on processing and decision-making.

Main Methods:

• Conducted two affective priming experiments manipulating word-emoji valence congruency.
• Analyzed behavioral data (speed, accuracy) and cognitive parameters using linear mixed-effects models.
• Applied the Drift Diffusion Model (DDM) to analyze information accumulation and processing efficiency.

Main Results:

• Emotional words reliably modulated emoji evaluation, showing a positivity bias for positive emojis.
• Emojis had a weaker, stage-dependent influence on word processing, mainly affecting later recognition phases.
• Emotionally congruent stimuli facilitated processing, while incongruent stimuli impaired performance and reduced processing efficiency (lower drift rates).

Conclusions:

• Demonstrated an asymmetric interaction: words exert a stronger influence on emoji processing than vice versa.
• Emojis function as meaningful affective cues, with their impact dependent on contextual alignment and task demands.
• Findings challenge the view of emojis as mere decorative elements, emphasizing their role in affective communication.