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Google Algorithm Discriminates Against Bad Reviews
j_col writes "According to the official Google blog, Google has altered their PageRank algorithm to not give back linking points to bad reviews of websites belonging to online retailers, following the publication of a recent article in the New York Times describing one woman's experiences in being harassed by an online retailer she found via Google. The specific changes to the algorithm are of course a guarded secret. So considering that these changes are already live, how do we know how the algorithm determines a bad review from a good one, and whether or not innocent online retailers will be wrongly punished by having their rankings downgraded?"
"Google has altered their PageRank algorithm to not give back linking points to bad reviews of websites belonging to online retailers"
Uh, no. Google changed it so that websites of poorly reviewed retailers lose points, not the reviews themselves.
"National Security is the chief cause of national insecurity." - Celine's First Law
Yes, but doing that takes longer than if they're provided with a list of criteria along with a scoring guide. It's not ideal, but it gives more time between adjustments and having to make a new adjustment because somebody has it figured out.
... not "bad reviews", which would be very anti-consumer.
Instead, the poorly reviewed products and services are going to lose index.
This kind of selective pressure will reward those companies whose services and products garner better reviews.
I just wonder if this will lead to more astroturfed reviews and payola for review-sites like Yelp.
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That's pretty buried. If I don't see what I'm looking for on the first page of results, I adjust my search terms, I don't click through to the second (of countless) page of results.
It may as well be.
http://www.marketingpilgrim.com/2008/04/iprospect-blended-search-study.html
There are studies that says that beyond the first page the majority of people don't bother continuing to search and use more words or different search engines.
The blog does not say what the contributor says it does. The closest it comes is noting that the links from the negative reviews never counted in the first place because the sites hosting the reviews used the "rel=nofollow" attribute on the links. What it does say is that they have altered the algorithm to punish bad businesses more effectively in response to the NYT article that suggested that being bad could be good for business.
Move along, nothing to see here!
They look for phrases like
... who feels like Google results have gotten really, really bad? I know it can come in waves as the SEO arms race progresses, but srsly. I feel like Google's user base has shifted from technical people to the average populace, and so have the results.
One hopes the guys at Google took into account the business that sets up a fake review site for the purpose of posting negative reviews of competitors to get Google to falsely downgrade them. My bet's on a manual filter to remove such sites, probably based on a discrepancy between those sites and every other review site.
This kind of selective pressure will reward those companies who can afford to pay people to destroy the page ranking of their competitors.
FTFY.
Yes, and in the article they acknowledge people are always trying to game their system. It's very clear that keeping it secret is done to delay gaming the system and to give them time to keep refining it.
Yes, someone will game it. Their response has been very reasonable.
The Kruger Dunning explains most post on
Google is the worst company ever. They sold out and went evil. I give their company a poor review and personal rating.
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Just disrupt the deflector shield with a tachyon burst.
Its a long interesting read.
Quite the character mr. Borker is.
http://www.nytimes.com/2010/11/28/business/28borker.html
This kind of selective pressure will reward those companies who can afford to pay people to destroy the page ranking of their competitors.
FTFY.
I thought about that but the article states that
an algorithmic solution which detects the merchant from the Times article along with hundreds of other merchants that, in our opinion, provide an extremely poor user experience
.. I presume this means that the weighting would not be linear, but more like an exponential dropoff when reviews are numerous, time-disjoint, and all negative. I'm sure Google has done at least a sample analysis using their mountain of data. I think the biggest point made here is that (as a vendor) services to monitor your product/service will become increasingly important so you can reply to negative reviews and actively manage any trolls... whether this leads to more engagement or simply more astroturfing is yet to be seen.
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You are guilty of reification. Information does not want to be free. Information does not want anything, because information is not a conscious entity capable of thought, desire, or volition. Treating abstract concepts as though they had thoughts, needs, or desires is faulty logic.
I write sci-fi for metalheads
I tried to post this earlier (guess I was too slow). But, considering that Google specifically said they would be looking into this later, that means: In the (paraphrased) words of Coots and Gillespie: They are making a list, And checking it twice; gonna find out who's naughty and nice"
excitingthingstodo.blogspot.com
There is. It's called the market, and they are rated #1. If their results start to suck, then people will switch to a different search engine, as has already happened once.
This sentence no verb.
I wrote my favorite escort a glowing review, all about how much and how hard she sucks, and now google is going to downrank her and it will be all my fault! This is terrible...
On a more serious note, correctly assigning "positive" or "negative" to a given adjective or phrase, across a wide range of subject areas, must actually be something that would give the computational linguists a bit of trouble(or 10,000 interns a very boring time of it)... Simply parsing star ratings or "out of 10" is easy enough; but is a vacuum cleaner that sucks good or bad?
This is the fundamental problem with "crowdsourcing" reviews. Where the number of reviewers is large compared to the number of items being reviewed, as with movies, it works fine. Where the ratio is small, it doesn't. It's far too easy to game the system. There are automated tools for that.
This problem has become worse since the October 27th change to Google, when Google Places/Maps results were merged into web search. This made "local" results much more prominent. Look at the first screen of Google search results for a local product or service. Most of what you see are Google Places results, maps, or ads. The organic results are so far down they don't matter.
As a result, the "black hat" SEO companies are now aggressively targeting Google's places and maps system. "Convert Offline" is quite open about this, with their article Dominating Google Maps- The Most Effective Spam Ever And What You Can Learn From It" In some ways, Google Places is more vulnerable to attack than organic search. The number of web mentions of a local business tends to be small, so the amount of phony material that has to be generated to make a business look good is also small. Each mention carries a lot of weight.
Google might lose this battle. Craigslist did. Back in 2008, Cory Doctorow wrote about "Spammers discuss breaking Craigslist verification system". It's become much worse since then. Personals were the first to go, and are now over 90% spam. Then Computer Services and Self Employment fell to the spammers. Jobs and Real Estate are under attack. Along the way, Gmail became a spam haven, especially after Jiffy Gmail Email Creator became widely used.
The fundamental design assumption of Google is that important stuff has lots of links to it. That's not a valid assumption in local search.
I think once a "review" is identified, and they have sucks, a$$h0le.... and a whole lot of other cuss words, its safe to say its a negative review.
Such reviews grouped by percentage vs those that don't have these cuss words would give you if the reviewed entity is bad or good and by how much. Further take these percentages and total count of reviews over a period of time, say per week for the last dozen or so week, normalize against volume trends (e.g. more volume during Chirstmas rush for retailer , you can tell if the entity is improving or becoming worst.
Now this may not be google's algorithm, however mine would look something like that.
Actually, it's kind of interesting how that article went up and then less than a week later Google changed their entire algorithm.... affecting millions of people. It's like they're reading Slashdot's mind man.... trippy.
How many more years will slashdot have an off-by-one error on your Score in your profile?
I had the same problem. I didn't understand WTF the summary was saying, so I had to RTFA.
Hey, wait a minute. googleblog.blogspot.com is gaming the system to get more pageviews, by getting people to post bad summaries to Slashdot!
Slashdot's editorbot should use the coherency engine on summaries, and if the summary doesn't make sense or has too much non-humorous ambiguity, it should penalize the linked articles.
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