How Community Pulse is built

The qualitative layer is built from four subreddits where people who live in, or are thinking about moving to, Dubai actually talk about neighborhoods: r/dubai, r/UAE, r/expats, and r/digitalnomad — a snapshot spanning 2021–2026.

The initial archive was extended with an authorised Arctic Shift export. The combined archive contains 23,330 area-item records sent to the AI scorer, with the latest collected item dated July 21, 2026. Deleted or removed content, off-topic chatter, non-Dubai locations, advertiser-heavy subreddits and property listings are excluded before publication.

After scoring and applying a confidence threshold (more on that below), 5,720 items cover 80 Dubai areas. Each area page shows you its own sample size and its trend over time.

Every post and comment goes through Anthropic's Claude Haiku 4.5. We give the model the item text plus the area it was tagged with, and ask it to return a structured JSON object:

• on_topic — is this actually about this area, or noise?
• sentiment — -1 (very negative) to +1 (very positive)
• aspects — up to four tags from a fixed vocabulary (price, traffic, community, noise, schools, etc.)
• pros / cons — up to three short paraphrased claims each
• persona_signal — resident, considering a move, investor, tourist, professional commenter, or unknown
• confidence — 0 to 1, how sure the model is

We only use items where on_topic = true AND confidence ≥ 0.5. The rest are discarded — typically about 30–40% of the raw sample. Area pages show both numbers so you can see the drop-off.

Sentiment for each area is the weighted mean of individual-item sentiment, weighted by confidence × log(1 + Reddit upvotes). High-confidence, well-upvoted comments carry more weight than low-confidence throwaway ones — but zero-score items still count.

The 3-year sentiment trend is a linear-regression slope over the last 4 available quarters of rolling sentiment, expressed per year.

Community Pulse is useful because it's the lived-experience signal that listings sites never show. But it has important limitations you should keep in mind.

Collection and scoring run periodically rather than live. Each area carries its own latest-source date, while the hub discloses the newest item in the combined archive and whether collection was complete.

Re-scoring the same items is wasteful, so the pipeline is incremental: new items get scored, existing items keep their original score unless we intentionally rerun them.

Methodology version: v1.1. If the scoring prompt, confidence threshold or weighting changes, the version increments and we'll note it here.

We flag communities reported flooded in the April 2024 event (Dubai's heaviest rainfall in ~75 years) with one of two tiers: Severe (prolonged standing water, evacuations) or Reported (waterlogging). Severity is a conservative editorial read of public reporting, with sources cited.

We deliberately do not derive flood risk from elevation. Dubai is flat and flooding is driven by storm-drainage capacity, not height — an elevation proxy mislabels low-lying coastal communities (Dubai Marina, Palm, JBR) that drain straight to the sea and did not flood, while the inland master-communities that did flood sit at higher elevation. So elevation is shown only as context, never as a risk score.

This is indicative only — not an engineering, drainage, planning or insurance assessment. There is no official public per-community flood dataset for Dubai, so this reflects public reporting of a single event. A community not listed was simply not reported flooded — that is not evidence of safety. Corrections welcome — email us.

If a pull quote misrepresents the thread it links to, or an area page draws a conclusion that the underlying posts don't support, we want to know. It sharpens the prompt and re-scores the offending items.

Email hello@dubuy.ai with:

• the area page URL
• the specific claim or quote
• what you think it should say instead (or a pointer to the Reddit thread that contradicts it)