HETEROPHILY

HETEROPHILY

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Exogamy

Exogamy is the social norm of mating or marrying outside one's social group. The group defines the scope and extent of exogamy, and the rules and enforcement mechanisms that ensure its continuity. One form of exogamy is dual exogamy, in which two groups continually intermarry with each other. In social science, exogamy is viewed as a combination of two related aspects: biological and cultural. Biological exogamy is the marriage of people who are not blood relatives. This is regulated by incest taboos and laws against incest. Cultural exogamy is marrying outside a specific cultural group; the opposite being endogamy, marriage within a social group.

In connection with: Exogamy

Exogamy

Description combos: of taboos intermarry regulated marrying and and defines in

Diffusion of innovations thumbnail

Diffusion of innovations

Diffusion of innovations is a theory that seeks to explain how, why, and at what rate new ideas and technology spread. The theory was popularized by Everett Rogers in his book Diffusion of Innovations, first published in 1962. Rogers argues that diffusion is the process by which an innovation is communicated through certain channels over time among the participants in a social system. The origins of the diffusion of innovations theory are varied and span multiple disciplines. Rogers proposes that five main elements influence the spread of a new idea: the innovation itself, adopters, communication channels, time, and a social system. This process relies heavily on social capital. The innovation must be widely adopted in order to self-sustain. Within the rate of adoption, there is a point at which an innovation reaches critical mass. In 1989, management consultants working at the consulting firm Regis McKenna, Inc. theorized that this point lies at the boundary between the early adopters and the early majority. This gap between niche appeal and mass (self-sustained) adoption was originally labeled "the marketing chasm". The categories of adopters are innovators, early adopters, early majority, late majority, and laggards. Diffusion manifests itself in different ways and is highly subject to the type of adopters and innovation-decision process. The criterion for the adopter categorization is innovativeness, defined as the degree to which an individual adopts a new idea.

In connection with: Diffusion of innovations

Diffusion

of

innovations

Title combos: Diffusion of Diffusion of innovations

Description combos: book between argues theory of of point the Rogers

Homophily thumbnail

Homophily

Homophily (from Ancient Greek ὁμός (homós) 'same, common' and φιλία (philía) 'friendship, love') is a concept in sociology describing the tendency of individuals to associate and bond with similar others, as in the proverb "birds of a feather flock together". The presence of homophily has been discovered in a vast array of network studies: over 100 studies have observed homophily in some form or another, and they establish that similarity is associated with connection. The categories on which homophily occurs include age, gender, class, and organizational role. The opposite of homophily is heterophily or intermingling. Individuals in homophilic relationships share common characteristics (beliefs, values, education, etc.) that make communication and relationship formation easier. Homophily between mated pairs in animals has been extensively studied in the field of evolutionary biology, where it is known as assortative mating. Homophily between mated pairs is common within natural animal mating populations. Homophily has a variety of consequences for social and economic outcomes.

In connection with: Homophily

Homophily

Description combos: intermingling etc formation and that is is of studies

Friendship thumbnail

Friendship

Friendship is a relationship of mutual affection between people. It is a stronger form of interpersonal bond than an "acquaintance" or an "association", such as a classmate, neighbor, coworker, or colleague. Although there are many forms of friendship, certain features are common to many such bonds, such as choosing to be with one another, enjoying time spent together, and being able to engage in a positive and supportive role to one another. Sometimes friends are distinguished from family, as in the saying "friends and family", and sometimes from lovers (e.g., "lovers and friends"), although the line is blurred with friends with benefits. Similarly, being in the friend zone describes someone who is restricted from rising from the status of friend to that of lover (see also unrequited love). Friendship has been studied in academic fields, such as communication, sociology, social psychology, anthropology, and philosophy. Various academic theories of friendship have been proposed, including social exchange theory, equity theory, relational dialectics, and attachment styles.

In connection with: Friendship

Friendship

Description combos: together time choosing are friendship exchange as the be

Heterophily

Heterophily (meaning "love of the different") is the tendency of individuals to collect in diverse groups; it is the opposite of homophily. This phenomenon can be seen in relationships between individuals. As a result, it can be analyzed in the workplace to create a more efficient and innovative workplace. It has also become an area of social network analysis.

In connection with: Heterophily

Heterophily

Description combos: become workplace in phenomenon workplace love result be of

Intermingling thumbnail

Intermingling

Intermingling, or heterophily, from a sociological perspective includes the various forms of interactions between individuals that go against a particular society's cultural norms. These relationships stem from weak or absent ties, which are contrary to strong ties and constitute of networks between individuals who know little or nothing about one another. Examples of intermingling can include networking, work-place romance, or cross-cultural dating.

In connection with: Intermingling

Intermingling

Description combos: place ties norms various or individuals the against go

Graph neural network

Graph neural networks (GNN) are specialized artificial neural networks that are designed for tasks whose inputs are graphs. One prominent example is molecular drug design. Each input sample is a graph representation of a molecule, where atoms form the nodes and chemical bonds between atoms form the edges. In addition to the graph representation, the input also includes known chemical properties for each of the atoms. Dataset samples may thus differ in length, reflecting the varying numbers of atoms in molecules, and the varying number of bonds between them. The task is to predict the efficacy of a given molecule for a specific medical application, like eliminating E. coli bacteria. The key design element of GNNs is the use of pairwise message passing, such that graph nodes iteratively update their representations by exchanging information with their neighbors. Several GNN architectures have been proposed, which implement different flavors of message passing, started by recursive or convolutional constructive approaches. As of 2022, it is an open question whether it is possible to define GNN architectures "going beyond" message passing, or instead every GNN can be built on message passing over suitably defined graphs. In the more general subject of "geometric deep learning", certain existing neural network architectures can be interpreted as GNNs operating on suitably defined graphs. A convolutional neural network layer, in the context of computer vision, can be considered a GNN applied to graphs whose nodes are pixels and only adjacent pixels are connected by edges in the graph. A transformer layer, in natural language processing, can be considered a GNN applied to complete graphs whose nodes are words or tokens in a passage of natural language text. Relevant application domains for GNNs include natural language processing, social networks, citation networks, molecular biology, chemistry, physics and NP-hard combinatorial optimization problems. Open source libraries implementing GNNs include PyTorch Geometric (PyTorch), TensorFlow GNN (TensorFlow), Deep Graph Library (framework agnostic), jraph (Google JAX), and GraphNeuralNetworks.jl/GeometricFlux.jl (Julia, Flux).

In connection with: Graph neural network

Graph

neural

network

Title combos: Graph network Graph neural network

Description combos: GNNs in layer GNN their can open exchanging to

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