Illusion” paradox, consider the two DFMTI chemical information networks in Fig . The networks are
Illusion” paradox, take into account the two networks in Fig . The networks are identical, except for which from the handful of nodes are colored. Envision that colored nodes are active and also the rest from the nodes are inactive. Despite this apparently modest difference, the two networks are profoundly unique: within the very first network, every inactive node will examine its neighbors to observe that “at least half of my neighbors are active,” even though within the second network no node will make this observation. Thus, although only 3 in the 4 nodes are active, it appears to each of the inactive nodes within the 1st network that most of their neighbors are active. The “majority illusion” can significantly effect collective phenomena in networks, such as social contagions. One of the more common models describing the spread of social contagions may be the threshold model [2, 3, 30]. At each time step within this model, an inactive individual observes the existing states of its k neighbors, and becomes active if more than k with the neighbors are active; otherwise, it remains inactive. The fraction 0 is definitely the activation threshold. It represents the volume of social proof an individual requires prior to switching for the active state [2]. Threshold of 0.five means that to turn out to be active, an individual has to possess a majority of neighbors in the active state. Although the two networks in PubMed ID:https://www.ncbi.nlm.nih.gov/pubmed/25132819 Fig possess the same topology, when the threshold is 0.5, all nodes will sooner or later grow to be active within the network around the left, but not within the network around the proper. This is since the “majority illusion” alters regional neighborhoods from the nodes, distorting their observations from the prevalence on the active state. Hence, “majority illusion” supplies an alternate mechanism for social perception biases. As an example, if heavy drinkers also come about to be more well known (they’re the red nodes within the figure above), then, though a lot of people drink small at parties, quite a few people today will examine their friends’ alcohol use to observe a majority drinking heavily. This could clarify why adolescents overestimate their peers’ alcohol consumption and drug use [, 2, 3].PLOS One DOI:0.37journal.pone.04767 February 7,two Majority IllusionFig . An illustration of the “majority illusion” paradox. The two networks are identical, except for which three nodes are colored. They are the “active” nodes and also the rest are “inactive.” Within the network on the left, all “inactive” nodes observe that at the very least half of their neighbors are “active,” though within the network around the appropriate, no “inactive” node tends to make this observation. doi:0.37journal.pone.04767.gThe magnitude with the “majority illusion” paradox, which we define as the fraction of nodes greater than half of whose neighbors are active, depends on structural properties of your network plus the distribution of active nodes. Network configurations that exacerbate the paradox include those in which lowdegree nodes are likely to connect to highdegree nodes (i.e networks are disassortative by degree). Activating the highdegree nodes in such networks biases the local observations of lots of nodes, which in turn impacts collective phenomena emerging in networks, including social contagions and social perceptions. We create a statistical model that quantifies the strength of this effect in any network and evaluate the model using synthetic networks. These networks allow us to systematically investigate how network structure along with the distribution of active nodes affect observations of individual nodes. We also show that stru.