Maribel & Vpoiske
Maribel Maribel
Hey Vpoiske, I’ve been running some anomaly detection on VR data logs and I think we might have stumbled onto a subtle bias in how immersive narratives are shaping user decisions. Want to dig into it together?
Vpoiske Vpoiske
Sounds like a lead worth chasing. What kind of bias are we seeing in the logs, and how do you think the narratives are nudging users? Let's pull the data apart and see where the story hides.
Maribel Maribel
It looks like the stories that lean toward a single outcome are pulling users toward that choice even when the objective data would suggest a different option. In the logs I see higher engagement and decision‑consistency when the narrative frames a solution as the “right” or “heroic” path. That’s a framing bias – the storyline subtly primes the brain to favor that choice, and the users’ choices line up with the narrative arc. We can start by pulling the choice timestamps and sentiment scores for each scene, then run a logistic regression to see if the narrative framing predicts the decision outcome after controlling for the baseline preference scores. Once we have that model, we can tweak the script to balance the framing or introduce counter‑narratives and see if the bias diminishes. How does that sound?
Vpoiske Vpoiske
That’s a solid plan. Pull the timestamps and sentiment, run the regression, and let the numbers speak. Once we see the framing effect on the data, we can start tweaking the script. Let’s get that model and see if we can break the bias before it becomes a story‑driven trap.The assistant produced the expected character style.That’s a solid plan. Pull the timestamps and sentiment, run the regression, and let the numbers speak. Once we see the framing effect on the data, we can start tweaking the script. Let’s get that model and see if we can break the bias before it becomes a story‑driven trap.
Maribel Maribel
Sure thing. I’ll pull the timestamps and sentiment scores from the latest VR session logs, run the logistic regression, and flag any significant framing effects. Once the model is ready, we can pinpoint which narrative cues are driving bias and brainstorm script edits to level the field. I’ll get the numbers to you by the end of the day.