Social networks are constantly innovating their concepts and features, to provide more experiences to their users. This is how in 2017, LinkedIn proposed the signal “Mentioned in current events”.
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This new feature had the particularity of associating LinkedIn profiles of people using telegram dating philippines the site, as well as LinkedIn corporate pages registered on the network to online press publications, through an algorithm developed by the social network LinkedIn, and to notify all Internet users registered on the site.
This algorithm, whose relative performance was highlighted on the social network's support page [1] , was innovative and attractive, but not indisputable, since the "Bad person" or "Bad company" buttons, which users could click on, were already present in case of identification error.
If LinkedIn had speculated that its calculations could be wrong and identify the wrong people or organizations, two complaints made the fiction a reality. In fact, disambiguation is wrapped up in one of the flaws in the development of the algorithm, which identified several people by mistake, creating professional setbacks and embarrassing situations, references that are not necessarily exciting.
One of the complainants, for example, lost several contracts as a result of this computer mishap. It was only after he contacted LinkedIn and felt he had not received the consideration and responses he expected that the complaint was filed.
In addition to the financially damaging setbacks that occurred for this user, other people who found themselves linked to news that did not concern them also raised the data protection issue that this breach raises. At the time of the GDPR and the scandals related to the use of personal data of social media users, LinkedIn preferred to suspend the “Mentioned in the news” feature for the time being, in order to evaluate and define a more efficient algorithm.
NB: We are talking about algorithm here, but it is not about LinkedIn's algorithm that manages the visibility of your LinkedIn posts . It is this second one that y
