Modern technology hasdrastically changed the way we interact and consume information. For example,online social platforms allow for seamless communication exchanges at anunprecedented scale. However, we are still bounded by cognitive and temporalconstraints. Our attention is limited and extremely valuable. Algorithmicpersonalization has become a standard approach to tackle the informationoverload problem. As result, the exposure to our friends’ opinions and ourperception about important issues might be distorted. However, the effects ofalgorithmic gatekeeping on our hyper-connected society are poorly understood.During the talk, I will discuss a model of opinion dynamics where individualsare connected through a social network and adopt opinions as function of theview points they are exposed to. I will consider various filtering algorithmsthat select the opinions shown to each user i) at random ii) considering timeordering or iii) her current opinion. Furthermore, I will analyze the interplaybetween such mechanisms and crucial features of real networks.
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