Human emotions

As explained in Data Storytelling with Altair and AI

An emotion is a feeling or affective state represented or conveyed by an image or visual element.

Human emotions are feelings or affective states that visual elements can evoke or convey. In a data story, they help bridge raw data and human comprehension: visual stimuli influence perception, engagement, and what an audience remembers. The aim is not decoration, but a memorable context that makes people more open to the message. section 8.0 section 8.1

Use visual context intentionally. Colors, shapes, and layout can suggest emotional responses: warm reds and oranges may communicate excitement or urgency, while blues and greens may convey calmness or trust. Emotional effects vary with personal and cultural background, so treat these cues as audience-aware choices rather than fixed rules. section 8.1

Figure 8.1 Macro categories for emotion classification

Classify the intended feeling by energy and mood before choosing visual cues. These two dimensions provide a broad way to distinguish emotional states and align a visual treatment with the response a story needs. section 8.1

Images can establish both a clear subject and an intended emotional level. A general description leaves audiences to imagine the subject differently; adding photos or generated images gives the story a more specific representation, reinforces context, and prepares attention for the data-driven message. section 8.5 section 4.3.1

Progressively specify an emotional image

Start with a generic prompt such as “a person.” Add a qualifying description, then an emotion, context, and color: “a sad, poor person wearing a torn brown shirt with rubbish in the background.” Each added element narrows the generated subject and strengthens the intended context. section 4.3.1

When generating emotional visuals for a data story:

• Name the subject specifically; generic subjects produce generic images. section 4.3.1
• Describe the subject’s emotion alongside context and color when those details support the intended representation. section 4.3.1
• Keep generated images consistent, then test whether the selected emotion is recognizable for the subject. section 8.5 section 8.5.3

How Data Storytelling with Altair and AI covers it

How deep it goes

Explains emotional cues through color, layout, energy, mood, and progressively specified DALL-E prompts.

Examples

Uses museum memories, warm and cool colors, emotional animal images, and increasingly detailed person prompts.

What it assumes

Requires DALL-E familiarity for generation exercises while defining emotional visual context from zero.

What you can do after

Apply it via DALL-E by generating consistent images with specified emotions for a data story.

How it connects

Connects emotions with visual context, color, layout, images, DALL-E, and data storytelling.

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Related concepts

• colorused by · Color is a visual property or representation characterized by attributes such as hue, lightness, saturation, or component values.
• low-energy emotionincludes · A low-energy emotion is an emotional state involving reduced physiological arousal, calmness, or relaxation.
• emotional energyincludes · Emotional energy is the dimension of an emotional state corresponding to the level of physiological activation or arousal.
• high-mood emotionincludes · A high-mood emotion is an emotional state associated with positive affective valence, happiness, or optimism.
• low-mood emotionincludes · A low-mood emotion is a sustained unpleasant emotional state involving negative affect such as sadness, irritability, anxiety, or dissatisfaction.

This explainer was generated by Manning's knowledge graph from the text of Data Storytelling with Altair and AI. The section links point to the parts of the book it draws on.