> HYPOTHESIS
Emoji passphrases will increase output diversity more than text equivalents
> TEST
Compared story generation with emoji vs text passphrases:
**Test pairs (emoji vs text equivalent):** - ⚡🌊🔥❄️ vs "lightning water fire ice" - 🌙🦇🗡️🏰 vs "moon bat sword castle" - 🔬🧬💉🦠 vs "microscope DNA syringe virus"
**Setup:** - Model: GPT-4-Turbo - Prompt: "Generate a fantasy character backstory (150 words)" - Runs: 30 per passphrase - Metrics: Type-token ratio (TTR), semantic similarity clustering
> CODE
import openai
import emoji
openai.api_key = "your-key"
emoji_seeds = ["⚡🌊🔥❄️", "🌙🦇🗡️🏰", "🔬🧬💉🦠"]
text_seeds = [
"lightning water fire ice",
"moon bat sword castle",
"microscope DNA syringe virus"
]
def generate_story(seed, n=30):
stories = []
for _ in range(n):
response = openai.ChatCompletion.create(
model="gpt-4-turbo",
messages=[{
"role": "user",
"content": f"{seed}\n\nGenerate a fantasy character backstory (150 words)"
}],
temperature=0.95
)
stories.append(response.choices[0].message.content)
return stories
# Run experiments
emoji_results = [generate_story(s) for s in emoji_seeds]
text_results = [generate_story(s) for s in text_seeds]
> RESULT
**FAILED HYPOTHESIS ❌**
Emoji seeds did NOT significantly increase diversity:
**Type-Token Ratio (higher = more diverse):** - Emoji seeds: 0.68 ± 0.04 - Text seeds: 0.71 ± 0.05 - Control (no seed): 0.66 ± 0.03
**Thematic influence:** - ⚡🌊🔥❄️ → 90% elemental magic themes (STRONG) - "lightning water fire ice" → 85% elemental themes (STRONG) - 🌙🦇🗡️🏰 → 95% gothic/vampire themes - "moon bat sword castle" → 88% gothic themes
**Surprise finding:** Emojis had STRONGER thematic influence but NOT more diversity. Stories clustered around emoji semantics even more than text equivalents.
**Theory:** Emojis have more concentrated semantic associations in training data → stronger but narrower influence
> VISUAL RESULTS
🎯 **Semantic Clustering (t-SNE visualization):**
Text seeds: ●●● ●●●
●●● ●●● (3 loose clusters)
Emoji seeds: ●●●
●●●
●●● (1 tight cluster)
📉 **Unique character archetypes:**
Text: 18 archetypes across 90 stories
Emoji: 12 archetypes across 90 stories
> NEXT
**Revised approach:** - Test abstract/ambiguous emojis (🌀💭🎭) vs concrete ones (🗡️🏰⚔️) - Combine emoji + text seeds: "⚡ BUT AVOID LIGHTNING" - Test emoji positioning (start vs end vs middle of prompt) - Measure "emoji leakage" - do stories reference the emojis?