How to learn to recognize fake reviews on the Internet?

Reviews of goods and ser­vices on the Inter­net are an ambigu­ous thing. They can be very use­ful, but they can also be fake. It often hap­pens that busi­ness own­ers and their friends them­selves write fake pos­i­tive reviews about prod­ucts or estab­lish­ments. How can you rec­og­nize such reviews? sci­en­tists saythat you already have a tool for this. This is your intu­ition.

The study of intuition

Sci­en­tists from York Uni­ver­si­ty (Cana­da) and Nanyang Tech­no­log­i­cal Uni­ver­si­ty (Sin­ga­pore) con­duct­ed a study involv­ing 380 vol­un­teers. The sub­jects had to rate the reviews on the pages of three hotels. Some of these reviews were real, some were fake. Par­tic­i­pants in the study had to rec­og­nize fake reviews. At the same time, they could rely on both gen­er­al intu­ition and pay atten­tion to the para­me­ters that are used by com­put­er algo­rithms to detect fake reviews.

The com­put­er algo­rithms that are used to weed out fake reviews tend to pay atten­tion to the detail of the review, the fre­quen­cy of superla­tive adjec­tives, and oth­er fea­tures that can dis­tin­guish a gen­uine review from a fake one. But sci­en­tists have found that peo­ple are sur­pris­ing­ly good at spot­ting fake reviews with­out any algo­rithms.

Of course, not every­one is equal­ly good. Fakes are best detect­ed by those who ini­tial­ly treat online reviews with a cer­tain amount of skep­ti­cism and do not trust every­thing that is writ­ten. And, accord­ing to sci­en­tists, it is in this slight skep­ti­cism that is the key to the prob­lem.

Slight skepticism

Sci­en­tists sug­gest that in order to effec­tive­ly iden­ti­fy fake reviews, peo­ple must ini­tial­ly be “tuned” to look for signs of decep­tion. For exam­ple, you go to the page of a restau­rant and see a series of acco­lades. At this point, you should ask your­self the ques­tion: “What if this restau­rant is not as good as these reviews say?”

Of course, busi­ness­es should stop writ­ing fake reviews. But we all know that it will nev­er stop. Mil­lions of peo­ple choose prod­ucts, hotels and cafes based on reviews from oth­er users. Obvi­ous­ly, this encour­ages com­pa­nies to fake tes­ti­mo­ni­als. At the moment, there is no tech­nol­o­gy that would allow 100% effec­tive screen­ing of fakes. But, accord­ing to sci­en­tists, your intu­ition works as well as, if not bet­ter than, exist­ing algo­rithms. And you can train her.

“Online users often fail to spot fake reviews because they don’t look for pre­emp­tive sig­nals of decep­tion. This habit needs to be changed. If the habit of look­ing at reviews with skep­ti­cism is prac­ticed long enough, users will even­tu­al­ly be able to rely on their intu­ition to detect fake reviews.”writes Dr. Sne­ha­sish Baner­jee, one of the authors of the study.

Also, sci­en­tists rec­om­mend try­ing to iso­late use­ful fac­tu­al infor­ma­tion from reviews. For exam­ple, the review “Break­fast was good” is not very infor­ma­tive. What exact­ly was good about him? What spe­cif­ic food was good? Spe­cif­ic details may indi­cate that the per­son real­ly knows what he is talk­ing about. You should also be wary of reviews that seem over­ly pos­i­tive or writ­ten in a false­ly casu­al style.

In gen­er­al, the rec­om­men­da­tion is sim­ple. “Turn on” skep­ti­cism and do not believe every­thing that is writ­ten on the Inter­net. Your intu­ition will do the rest for you.