London, March 3 (SocialNews.XYZ) While booking a hotel online, travellers should trust their gut instinct rather than relying on computer algorithms to figure out between fake and genuine reviews posted online, say researchers.
The study, published in the journal Information & Management, suggests that a greater awareness of the linguistic characteristics of 'fake' reviews can allow online users to spot the 'real' from the 'fake' for themselves.
"We often assume that the human brain is no match for a computer, but in actual fact there are certain things we can do to train the mind in approaching some aspects of life differently," said researcher Snehasish Banerjee from the University of York in the UK.
For the study, the team involved 380 people to respond to questions about three hotel reviews -- some authentic, others fake -- based on their perception of the reviews.
The users could rely on the same cues that computer algorithms use to discern 'fake' reviews, which includes the number of superlatives in the review, the level of details, if it was easy to read, and appeared noncommittal.
For those already sceptical of online reviews this was a relatively straightforward task, but most could not identity factors such as 'easy to read' and 'non-committal' like a computer algorithm could. In the absence of this skill, the participants relied on 'gut instinct'.
"The outcomes were surprisingly effective," Banerjee said.
"Following this study, we are recommending that people need to curb their instincts on truth and deception bias -- the tendency to either approach online content with the assumption that it is all true or all fake respectively -- as neither method works in the online environment," Banerjee added.
According to the researcher, online users often fail to detect fake reviews because they do not proactively look for deception cues.
"There is a need to change this default review reading habit, and if reading habit is practised long enough, they will eventually be able to rely on their gut instinct for fake review detection," Banerjee noted.
Source: IANS
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