Review sources
Analysing TripAdvisor reviews
People write longer and later on TripAdvisor than anywhere else. That changes both what these reviews are worth and what can be learned from them.
The character of this source
Reviews are longer, more often comparative ("better than the one next door") and written with a delay — sometimes weeks after the stay. That makes them excellent for catching repeating patterns and poor at noticing that something broke last week.
A lot of text per review
The share of reviews with no words is lowest here. Practically every statement carries something classifiable — the corpus is smaller but denser.
Comparisons with other venues
Authors set the venue against competitors unprompted. It is the only source where such a comparison appears without being asked for.
A delay in time
The report weighs the date of the stay, not only the date of publication. Without that the trend would shift by weeks and show improvement where there is none yet.
Step by step
How we use this source
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1
You point at the profile
A link to the property or the restaurant. The fetch works the same for accommodation and for dining.
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2
We weigh the date of the stay
Reviews here appear with a delay — sometimes weeks after the visit. The trend runs on the stay date rather than the publication date; otherwise it would shift by weeks.
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3
We exploit the length
The share of reviews with no text is lowest here, so practically every statement contributes. The corpus is smaller but denser than anywhere else.
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4
We merge with the other sources
Statements enter one corpus, but each quote on a problem card shows its platform. A signal confirmed across sources gets a marker.
In practice
The only source with comparisons nobody asked for
Authors on TripAdvisor set the venue against competitors of their own accord — "better than the place across the street", "pricier than a similar place last year". Sentences like these appear nowhere else and are the closest thing to market research that can be pulled out of reviews.
longest
reviews of all four platforms. The corpus is smaller, but every statement carries more to classify.
Why it works this way
Strongest paired with Google Maps
TripAdvisor gives the densest material of any platform — the most text per review and the most competitor comparisons, none of which anyone had to prompt. Google Maps gives scale and a wide spread of topics. Together they show both the repeating pattern and its size today, which is why both sources enter one corpus in the report.
Common questions
Does TripAdvisor cover restaurants too?
Yes, and we pull them the same way as accommodation. In hospitality this source is sometimes more valuable, because the reviews run longer than on Google Maps.
Do competitor comparisons from these reviews enter the report?
They appear as quotes on cards, but we build no metric from them. "Better than the place next door" is an opinion about someone else's venue and we have no way to verify it.
How do you combine these with the rest?
They enter one corpus and one classification, but each quote on a problem card shows which platform it came from. A confirmation marker appears when the same signal recurs across sources.
See also
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