trustiser

All About Trust and Reputation in the Digital World

Tag: Online Reviews

The Rise of the Digital Advisor

The Rise of the Digital Advisor

As the digital exodus is now well underway, a growing number of digital services offer the possibility to benefit from the reviews, opinions, and insights of knowledgeable people.  Indeed, all types of review sites (general-purpose review sites such as Yelp, specialized review sites such RateMDs, individual-oriented review sites like Dunwello, etc.) are more and more attracting reliable, insightful reviewers.  Those reviewers form an ever-strengthening community of digital advisors.  Their individual and collective knowledge and intelligence give the consumer a valuable, instantly available, continuously updated source of advice that covers virtually all topics.

Moreover, an increasing number of paid services, like JustAnswer, offer the possibility to submit online questions to advisors selected through a stringent vetting process.

In addition, digital genome sequencing, that is the ability to analyze and interpret digital footprints left by our daily activities in the digital world, will be increasingly used to detect, on a topic-basis, competent, reliable advisors.  Specialized services, such as Trustiser, will use digital genome sequencing techniques to offer the consumer the opportunity to tap into the wealth of knowledge and wisdom of those trusted advisors.

As a result of this major shift, the consumer intelligence is improving dramatically.  In other words, consumers now have the possibility to make informed critical or lifestyle-driven decisions, solve efficiently problems or discover otherwise unseen opportunities, in relation to a wide range of themes such as healthcare, home life, outdoor life, travel, financial services, and education.

Rafik Hanibeche & Adel Amri (Trustiser Founders)

Online Advertising and Trust

Online Advertising and Trust

A recent study, based on responses from 58,000 respondents in the US and 16,000 respondents in Europe, conducted by Forrester Research reveals interesting findings about the trust placed by consumers in various online advertising and promotion approaches (see figure below).  The study shows that 70% of consumers in the US (61% in Europe) trust brand or product recommendations from friends and family. While 55% of US consumers (33% in Europe) trust professionally written online reviews and 46%  of US consumers (38% in Europe) trust consumer written online reviews.

Forrester

As outlined in a previous post in this blog, this level of trust in friends and online opinions doesn’t come as a surprise.  It is the logical result of the good reputation that any person tends to have among his friends and the natural trust that online consumers place in authoritative reviewers and aggregated ratings (the so-called wisdom of crowds).  Both friends and online authoritative and aggregated opinions can be viewed as reliable sources.  The recommendations from reliable sources are of primary importance, they help human brain in making decisions very quickly because they have a big impact on trust inference.

That is the reason why we do think that the digital world should move towards the establishment of topic-related, experience and/or expertise-oriented, trust-based hierarchies of reviewers.  Those hierarchies will significantly reinforce, for the better, consumers’ reliance on online reviews and recommendations.

Rafik Hanibeche & Adel Amri (Trustiser Founders)

Rating the Raters

Rating the Raters

Rating services are playing an increasingly important role in the digital world as more and more individuals rely on these services to plan for the future, that is make critical or life-style-driven decisions, solve problems or discover opportunities.  In this context, the success of rating services will depend to a large extent on their ability to establish a trusted relationship with their users.

As a matter of fact, existing rating services generate a great deal of distrust among their users because they are fed by humans who all too often are able to discover and use the flaws in the algorithms that underpin current rating services.  In addition, current rating services place the same amount of trust in all users, regardless of their sincerity and the level of their experience or expertise-linked knowledge.  On top of that, businesses are devising strategies of all sorts to exert an influence on their customers’ ratings and reviews. Some businesses have gone so far as to pay targeted customers to get positive ratings and reviews.

Basically, there are two major issues that need to be addressed:
– Existing rating services are not able to defend themselves against individual and collaborative fake ratings and reviews, and thus are subject to manipulation.
– There is a lack of models to manage efficiently the trust placed in each rater.

Let’s take a closer look at each of these issues.

The inability to counter fake ratings

According to Bing Liu, a computer science professor at the University of Illinois at Chicago and a leading researcher in the area of fake online ratings, “for some products, up to 30 percent of ratings can be fake”.  Moreover, according to Gartner, by 2014, 10 to 15% of online ratings will be fake and paid for by companies. Fake ratings and reviews, a very cheap way of marketing, can be either excessively negative, bashing competitors’ products, services or brands, or overly positive,  raving about the products, services or brands of specific businesses.
Fake ratings and reviews can be published directly by businesses or posted by customers who receive perks for their contributions. Fake ratings and reviews can also be obtained by relying on professional favorable ratings providers.

A lot of effort and money are spent in research and development to rise to the challenge and devise mathematical models that detect and combat fake ratings and reviews.  For example, a team of researchers from the University of Rhode Island is underway with a project to develop algorithms that can serve as a defense against collaborative, profit-driven manipulations of online rating services.

The lack of models to manage trust placed in raters

The raters space is completely “flat” in existing rating services, and there is no hierarchy in terms of competence, that is experience or expertise-linked knowledge.  Moreover, current rating services are not intrinsically organized to attract competent raters.  As a result, everyone can rate anything in any domain.  Although some rating services include features aimed at tracking raters’ activities and giving a competence-based weight to each rating, we are far from addressing this issue adequately and effectively.

At this point, it is interesting to draw a parallel with Google’s search engine.  Considering that the web is a graph of documents, the power of Google’s search engine algorithms revolves around assigning a reputation index (a Page Rank) to each document and classifying the documents by their reputation inside the graph.  These algorithms not only take into account  the number of documents linking to a given document, but they also consider that a document partially inherits the reputation assigned to the documents that point to it.

If we consider the analogy with the graph of documents, rating services should include a graph of raters and implement algorithms similar to Google’s Page Rank algorithms.  But assigning a reputation index to each rater in the graph of raters through incoming reference count would not be sufficient to estimate the real reputation of a rater because:
– The graph of raters is more complex.  Reference counting alone is not sufficient to express this complexity.  The type of relationship a rater has with other users and the level of influence he exerts within the community of users should also be taken into account.
– The reputation index shouldn’t be considered as a single scalar number because when we look at the graph of raters from the angle of knowledge, the graph lives in multi-dimensional space, each domain of knowledge should be considered as a dimension, and reputation index should take the form of a vector.

In summary, although there is a great deal of effort to make rating services more reliable, the accomplishment of this goal is a long way off.
We do believe that a pure algorithmic approach is not sufficient to fix all these problems.  There is a need to combine a computational approach with a human controlling effort in order to substantially improve the overall trustworthiness of rating services.

Rafik Hanibeche & Adel Amri (Trustiser Founders)

Online Reviews and Trust

Online reviews and trust

A survey conducted in 2011 by Nielsen shows very interesting findings regarding trust and reputation in the digital world.  The survey was conducted between August 31 and September 16, 2011 and polled more than 28,000 online consumers in 56 countries throughout Asia Pacific, Europe, Latin America, the Middle East, Africa and North America.  The results of the study were released in April 2012.

The survey reveals that online consumer reviews are the second most trusted form of advertising with 70% of global consumers surveyed online indicating they trust them, an increase of 15% in 4 years.  While 92% of consumers around the world say they trust earned media, such as word-of-mouth and recommendations from friends and family, above all other forms of advertising.

Overall, the survey shows that consumers around the world continue to see recommendations from friends and online consumer opinions as by far the most credible.

This level of trust in friends and online consumer opinions doesn’t come as a surprise.  It is the logical result of the good reputation that any person tends to have among his friends and the natural trust that online consumers place in authoritative reviewers and aggregated ratings (the so-called wisdom of crowds).  Both friends and online authoritative and aggregated opinions can be viewed as reliable sources.  Recommendations from reliable sources are of primary importance, they help human brain in making decisions very quickly because they have a big impact on trust inference.

In this context, we do strongly believe that the digital world should move towards the establishment of formalized hierarchies of reviewers that are topic-related, experience and/or expertise-oriented and trust-based.  Those hierarchies will significantly reinforce, for the better, online users’ reliance on online reviews and recommendations.

Rafik Hanibeche & Adel Amri (Trustiser Founders)