Essay On Online Reviews





How Much Do You Trust Online Reviews?

          You’ve got a paper due by the end of the week and, of course, your computer is broken beyond repair. You may have been considering a new computer for some time now but where do you begin? If you’re like most young adults today, you may start with looking up some online reviews to compare different laptops, tablets, and computers to find out which one better suits your individual needs.

          When it comes down to online reviews, we tend to rely on real consumer experiences to help us make our choices between products that we are not familiar with. When someone we know and trust, like a friend or family member, recommends a laptop they’ve used for school, you probably feel more comfortable making that purchase. However, since we do not know the individuals behind the online reviews, we may have difficulty establishing trust in the review (Xu).

          This makes sense though, as we wouldn’t trust the review of a stranger on the street over our best friend. Online companies are aware of this and they have begun using strategies to give their reviewers perceived personalities (Mohammadi, Park, Sagae, Vinciarelli, Morecny). This concept can be seen on popular review-based websites where reviewers have profiles set up that include their name, location, interest, and photos. These websites also allow individuals to "rank-up” based on how many reviews they have and how helpful other users found that review. This kind of social media creates similarities between the reviewers and the product users, and the similarities increase the amount of trust that the product user has in the reviewer and, relatedly, in the review itself.

          What happens when we establish trust with these perceived personalities but later find out that they are fake? This is happening more and more in this consumer review-filled society as websites have created algorithms to sporadically post fake reviews of their product or service (Glance, Liu, Mukherjee). This strategy is ironically having the opposite effect on consumers as instead of establishing trust in the reviewer, consumers are more likely to be skeptical of the reviews and lose trust in the company (Glance et al.).

          Online reviews are found to have more trust when they are posted on private social media sites like a friend's Facebook or Twitter account. Aside from the actual trust you may form when you have a relationship of some kind with an individual, another reason that reviews posted on social media are more trustworthy to possible consumers is because they are unprompted (Mohammadi et al.). This leads the possible consumer to believe that the reviewer had such a sincere positive or negative experience with the company that they felt compelled to take time on their own to leave an honest review (Mohammadi et al.).

          How much you trust online reviews have little to do with the reviews and much to do with your trust in the person leaving the review. A better sense of trust, even if it is just perceived trust in an anonymous individual, will directly correlate to a trusted review of any product or service a company is offering. It is crucial to keep in mind that companies may be aware of this correlation and therefore may create fake personalities to leave ‘trustworthy’ reviews in order to boost their own popularity and sales.



Works Cited

Glance, Natalie., Liu, Bing., Mukherjee, Arjun. Spotting fake reviewer groups in consumer reviews. WWW ’12 Proceedings of the 21st international conference on the World Wide Web, 2012, pp. 191-200. https://dl.acm.org/citation.cfm?doid=2187836.2187863. Accessed 9 Dec. 2018.

Mohammadi, G., Park, S., Sagae, K., Vinciarelli, A., & Morency, L. Who Is Persuasive? The Role of Perceived Personality and Communication Modality in Social Multimedia. In Proceedings of 15th International Conference on Multimodal Interaction, pp. 19–25. Sydney, 2013. doi:10.1145/2522848.2522857

Xu, Q. Should I trust him? The effects of reviewer profile characteristics on eWOM credibility. Computers in Human Behavior, 33, 2014, pp. 136–144. doi:10.1016/j.chb.2014.01.027

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