No doubt you are hardly shocked to be told that many online reviews you come across online are phony. And the issue is not a new one at all, as evidenced by the today's lawsuit filed by Amazon against over 1,000 users who received compensation for posting 5 star reviews for a variety of books and other products.
And despite the efforts of Amazon and others to prohibit and prevent the creation of fake reviews, it's unlikely--probably impossible in fact--to eliminate these entirely.
But everyone, and not just business researchers, has an interest in developing a level of information literacy to better understand how to spot reviews that are most likely to be authentic, and most likely to be a fake. That's going to be the most sustainable and elegant solution to avoid getting fooled by fake reviewers.
Here are a variety of strategies you can take to help you better evaluate reviews from unknown persons on the Web:
• Note whether there are there lots of reviews for the
item or only a few. In general, the greater the number
of reviews, the less likely that a small number of phony
reviews can impact the aggregate score. That's why a site
like TripAdvisor, which receives and then averages many
thousands of reviews, is often so useful.
• Try to find out what interest—particularly financial—there
might be in creating fake reviews for that category and
adjust your skepticism meter accordingly. For example,
there is little financial interest in pumping up positive
ratings of, say, the tastiest recipes for homemade salsa,
but there certainly would be for competing hotel chains.
• If you are mostly interested in learning the pros and cons
of a reviewed item, consider ignoring the one- and five star
ratings, as these have a higher likelihood of being
phony, and read the threes and fours to get more nuanced
And when looking at any single review, ask yourself:
• Does the review site provide some kind of authority
badge, indicating that this review was written by a person
whose identity can be verified? If so, that’s a big plus. If
not, try to find out a bit about the person yourself, such
as where else this person has written reviews. Sometimes
you can click on a person’s name to find his or her other
reviews. Or, when it is worth your time and the reviewer
has an associated name or handle, you can search that
name online to try to find the other reviews yourself. If
you can discover more about a reviewer, try to address the
• How long have they been writing reviews? Someone
who has been writing reviews for several years is
probably less likely to be a shill than a brand-new
• What kinds of products do they review? The most
suspicious are people writing very positive (or negative)
reviews on a single product and doing so on multiple
review sites. One trustworthy type are reviewers who
focus on a specific niche (e.g., the person regularly
reviews all types of newly released cameras) and also
display a clear in-depth expertise on their subject and
share lots of nitty-gritty details. But someone who
reviews a wide range of products may be trustworthy
too, as it may indicate that they are not shilling for a
specific company. It’s a tough call!
• Another potentially useful strategy is to seek out and
read other reviews by the same reviewer, in particular
to see if he has evaluated something you have
personally used and are familiar with. Does the analysis
confirm or is in synch with what you already know?
The above strategies--and others and useful analysis tools--are discussed in my upcoming book, Find it Fast: Extracting Expert Information from Social Networks, Big Data and More, to be published next month by Information Today Inc/CyberAge.
What are your strategies for evaluating reviews from unknown sources? Please share them here!
There's been a variety of articles and discussions recently about the expected eventual replacement of keyword searching as our means for finding answers and information, and the rise of the automated "Intelligent Personal Assistant" that can anticipate what we need and want and then even go ahead and complete the desired tasks we want to complete.
These assistants--which today are probably best represented by Apple's Siri, Microsoft's Cortana and Google's Google Now--work by examining and crunching mountains of data about our own profile and data around us and engage in probabilistic analyses to make its predictions. That ingested data can include, for example, our past search history, our social media profile, our current location, our digital calendar, our past online preferences, and countless digital signals surrounding us embedded in objects.
There is even an excellent and compelling book on this development, written by Stefan Weitz, (Weitz had been the director of Microsoft Search) titled Search: How the Data Explosion Makes Us Smarter. In the book, Weitz goes into great detail on the promise of how what we mean by search will change based on this revolution in online searching.
As part of a recent interview I conducted with Weitz in the September 2015 issue of The Information Advisor's Guide to Internet Research, we described the forecast capabilities of the personal intelligent assistant like this:
So, say you are at a hotel and ready to go to a conference. Today you might go online and look up the location, then call for a cab, and make sure you’ve ordered breakfast via room service in enough time to get there for the first meeting. But in the new search environment, your digital assistant will have your favorite “on the road” room service breakfast ordered at the right time to your room, a cab called and ready, and a digital display of the address of the hotel for you to give the cab.
So for this week's blog I just want to pose a question: one can imagine a variety of consumer-oriented applications like the above for an intelligence personal assistant, but are there possibilities for business researchers? Could this be useful for finding information on companies, industries, new technologies, market research, patents/copyrights, trade, international statistical information and so on. If so, what would this look like?
I'd be grateful to hear from you on your speculations on what the potential is, if any, of the personal intelligent assistant for the business researcher.
A blog by Robert Berkman, editor Best of the Business Web