Google Sentiment Analysis: For Breakfast
Computer-judged sentiment analysis is about as reliable as a Met Office weather forecast. A Met Office weather forecast barked-out by a stolen Jack Russell in the absence of anyone else who knows better. And the dog has had catnip.
Still, Google has recently jumped on the bandwagon by adding sentiment analysis to Google Map reviews. But does the industry-leading search engine perform any better than a spaced-out terrier? Is sentiment measured with any reasonable level of accuracy?
Let’s find out. Let’s find out now. And let’s stick to the dog theme.
There were no sentiment analysis reports on kennels; most reviews are of restaurants and hotels. So, I’ve tenuously chosen to analyse the sentiment reports of ‘GreyStoke House’, a pet-friendly hotel situated in the idylls of the Lake District.
Before looking at the comments, it’s worth explaining that Google seems to pick out categories based on keywords within comments and reviews. Therefore, if a high proportion of reviews mention the word ‘hosts’ (as below), this becomes a category that reviews are extrapolated from.
These reviews are also chosen from a seemingly consistent and authoritative database of sites. TripAdvisor – one of the most respected travel communities on the web – features in most review listings, and most of the others sites are similarly respected and recurrent.
Moving on to the reviews, clearly the breakfast in this place is spectacular. Just look at the comments:
This many mentions of ‘breakfast’ has created a unique category. We can see that this morning meal is clearly life-changing, but what does Google think?
Superficially, the analysis is good. Most comments are positive (apart from the last if you’re a dog or dog-owner) and the sentiment gauge is accurate. So far, so good.
Second example: The ‘Dog House Hotel’ in Oxfordshire, “looks nice” but there’s a stunning caveat – “don’t expect to feel full after a meal”. The sentiment analysis reveals a shakier system than the first example.
For instance, the sentiment gauge for the ‘dining’ category is full despite the presence of some negative comments. One, regarding a cheesecake, is savage:
“The cheese cake desert was still half frozen, and the coffee cold.”
There are a few other interesting patterns to note. While some comments are ambiguously judged, others – like the enigmatically psychedelic comments below – are explicitly marked with sentiment.
1. “Negative: Room 7. Think should be put out of use.” – booking.com
2. “Positive: The wood effect surrounds of the room.” – booking.com
It’s also unclear whether the comments are being analysed in isolation, or the within the context of the overarching reviews. There’s little comment from Google on this, so inferences have to be made. This lack of transparency makes analysis difficult. There’s very little information beyond vague cryptic comments.
For me, the overall insight is in Google’s general approach. There are a few main strands to consider here. Google has achieved:
a) A decent grasp and understanding of which sites are authoritative in their field
b) The ability to determine what constitutes a review or subjective piece of commentary
c) The ability to (quite accurately) group comments semantically, based on keyword mentions
d) A basic grasp of sentiment
Conclusion
These insights speak volumes. The keyword-worshipping Google of old is evolving: interpreting conversations, analysing sentiment, collecting subjective information, and (potentially) assimilating this information into results.
The pretentious dandy!
Actually, why not? It makes sense. This information has to be included to produce better results.
The future will reveal how accurate this interpretation can be.
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Renaud JOLY
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