Social Intelligence - Turns Out, the Comments Section Is the Real Focus Group
Courtesy of The SILab: https://www.thesilab.com/
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Last week, I had the chance to attend the Observe Summit in Los Angeles, CA, hosted by The Social Intelligence Lab — a community of people who don’t just use social data, but genuinely care about the stories and signals living inside culture. It felt good to be back in a room full of researchers, strategists, analysts, and curious minds who think deeply about how people express themselves online. I reconnected with former colleagues I hadn’t seen in years, swapped war stories and wins, and made new connections with people who are actively shaping what this field will become next. There was a sense of collective momentum — like the work is evolving in real time and we’re doing it together.
The summit delivered two days of practitioner-led conversations about turning cultural noise into foresight and action.
Day 1: Explored fandoms, overlapping identity ecosystems, and how analyzing social video (plus the comments under the video) helps us move past dashboards and into meaning.
Day 2: Zoomed in on data quality, platform fragmentation, and building systems that combine AI + human judgment in ways that feel responsible and grounded.
The throughline?
This field is changing — quickly — and in a way that feels energizing. The work is moving away from surface-level “mentions tracking” and toward richer cultural understanding. The challenge (and opportunity) is to bring creativity, ethics, and rigor to how we build and communicate insights.
Key Learnings from Observe Summit
Fandom > Demographics
Identity isn’t a spreadsheet column. Real engagement happens when we understand the lore — the inside jokes, shared symbols, language, rivalries, and emotional investment that define communities. Listen first; collaborate second.
From Personas to Ecosystems
People are fluid and situational. Who you are on Reddit at midnight isn’t who you are on LinkedIn at noon. We need segment models that reflect dynamic, overlapping identities, not static audience boxes.
Foresight is a Practice, Not a Deliverable
Track micro-signals and macro-shifts in parallel. Build scenario plans. Use AI to accelerate synthesis, not replace the interpretive judgment that only humans have.
Social Video is the New Fieldwork
The comments are often more revealing than the content. And sentiment doesn’t “stick” — it evolves. The insight cycle continues after launch.
Trustworthy Data > More Data
Data quality is not a nice-to-have. Validate sources. Diversify inputs. Combine AI bot detection with human review. Transparency builds credibility — internally and externally.
What I appreciated most was being reminded that social intelligence has always been about people — their context, their creativity, their contradictions, their humor, their hopes. AI is here and it’s powerful, but its value depends entirely on how well we interpret, refine, and apply what it helps us see.
I left both grounded and inspired — proud of where this field is heading and grateful to be part of a community that pushes the work forward with curiosity, rigor, and heart.
Already looking forward to next year!
