Nothing Special   »   [go: up one dir, main page]
Scribd Logo
Upload

Welcome to Scribd!

  • 49 views

    Neural and Social Networks

    Uploaded by

    Vincent Miles Sustiguer
    Neural networks are computational systems modeled after the human brain that are used in artificial intelligence. They consist of interconnected nodes that process information using weighted connections. Modern neural networks have thousands to millions of nodes and connections, though still less complex than the human brain. Social networks are social structures made up of individuals or groups connected by relationships. Social network analysis studies these structures and patterns of connections. Popular social networking sites like Facebook, Instagram, and Twitter allow people to connect and share information online for both social and business purposes. Marketers use social media to engage customers and increase brand awareness.

    Copyright:

    © All Rights Reserved
    Download as DOCX, PDF, TXT or read online from Scribd

    Neural and Social Networks

    Uploaded by

    Vincent Miles Sustiguer
    49 views6 pages
    Neural networks are computational systems modeled after the human brain that are used in artificial intelligence. They consist of interconnected nodes that process information using weighted connections. Modern neural networks have thousands to millions of nodes and connections, though still less complex than the human brain. Social networks are social structures made up of individuals or groups connected by relationships. Social network analysis studies these structures and patterns of connections. Popular social networking sites like Facebook, Instagram, and Twitter allow people to connect and share information online for both social and business purposes. Marketers use social media to engage customers and increase brand awareness.

    Original Description:

    Original Title

    NEURAL AND SOCIAL NETWORKS

    Copyright

    © © All Rights Reserved

    Available Formats

    DOCX, PDF, TXT or read online from Scribd

    Did you find this document useful?

    Is this content inappropriate?

    Neural networks are computational systems modeled after the human brain that are used in artificial intelligence. They consist of interconnected nodes that process information using weighted connections. Modern neural networks have thousands to millions of nodes and connections, though still less complex than the human brain. Social networks are social structures made up of individuals or groups connected by relationships. Social network analysis studies these structures and patterns of connections. Popular social networking sites like Facebook, Instagram, and Twitter allow people to connect and share information online for both social and business purposes. Marketers use social media to engage customers and increase brand awareness.

    Copyright:

    © All Rights Reserved
    Download as DOCX, PDF, TXT or read online from Scribd
    Download as docx, pdf, or txt
    49 views6 pages

    Neural and Social Networks

    Uploaded by

    Vincent Miles Sustiguer
    Neural networks are computational systems modeled after the human brain that are used in artificial intelligence. They consist of interconnected nodes that process information using weighted connections. Modern neural networks have thousands to millions of nodes and connections, though still less complex than the human brain. Social networks are social structures made up of individuals or groups connected by relationships. Social network analysis studies these structures and patterns of connections. Popular social networking sites like Facebook, Instagram, and Twitter allow people to connect and share information online for both social and business purposes. Marketers use social media to engage customers and increase brand awareness.

    Copyright:

    © All Rights Reserved
    Download as DOCX, PDF, TXT or read online from Scribd
    Download as docx, pdf, or txt
    of 6

    NEURAL AND SOCIAL NETWORKS

       

         Neural networks (also referred to as connectionist systems) are a computational


    approach, which is based on a large collection of neural units (AKA artificial neurons),
    loosely modeling the way a biological brain solves problems with large clusters of
    biological neurons connected by axons. Each neural unit is connected with many others,
    and links can be enforcing or inhibitory in their effect on the activation state of
    connected neural units. Each individual neural unit may have a summation function
    which combines the values of all its inputs together. There may be a threshold function
    or limiting function on each connection and on the unit itself: such that the signal must
    surpass the limit before propagating to other neurons. These systems are self-learning
    and trained, rather than explicitly programmed, and excel in areas where the solution
    or feature detection is difficult to express in a traditional computer program.
         Neural networks typically consist of multiple layers or a cube design, and the signal path
    traverses from front to back. Back propagation is where the forward stimulation is used to
    reset weights on the "front" neural units and this is sometimes done in combination with
    training where the correct result is known. More modern networks are a bit more free flowing
    in terms of stimulation and inhibition with connections interacting in a much more chaotic
    and complex fashion. Dynamic neural networks are the most advanced- in that they
    dynamically can, based on rules, form new connections and even new neural units while
    disabling others.
         The goal of the neural network is to solve problems in the same way that the human brain
    would, although several neural networks are more abstract. Modern neural network projects
    typically work with a few thousand to a few million neural units and millions of connections,
    which is still several orders of magnitude less complex than the human brain and closer to
    the computing power of a worm.

    SOCIAL NETWORKS
      
          A social network is a social structure made up of a set of social actors (such as
    individuals or organizations), sets of dyadic ties, and other social interactions between
    actors. The social network perspective provides a set of methods for analyzing the structure
    of whole social entities as well as a variety of theories explaining the patterns observed in
    these structures. The study of these structures uses social network analysis to identify local
    and global patterns, locate influential entities, and examine network dynamics.
    Social networks and the analysis of them is an inherently interdisciplinary academic field
    which emerged from social psychology, sociology, statistics, and graph theory. Georg
    Simmel authored early structural theories in sociology emphasizing the dynamics of triads
    and "web of group affiliations". Jacob Moreno is credited with developing the
    first sociograms in the 1930s to study interpersonal relationships. These approaches were
    mathematically formalized in the 1950s and theories and methods of social networks became
    pervasive in the social and behavioral sciences by the 1980s. Social network analysis is now
    one of the major paradigms in contemporary sociology, and is also employed in a number of
    other social and formal sciences. Together with other complex networks, it forms part of the
    nascent field of network science.
    Posted by Darren Mabagos at 10:48 PM 
    Email ThisBlogThis!Share to TwitterShare to FacebookShare to Pinterest

    8 comments:

    1.

    nencyApril 20, 2019 at 3:40 AM

    It is a great website.. The Design looks very good.. Ke


    neural network is a network or circuit of biological neurons, or, in a modern sense, an artificial
    neural network, composed of artificial neurons or nodes.[1] Thus, a neural network is either
    a biological neural network, made up of biological neurons, or an artificial neural network, used for

    solving artificial intelligence (AI) problems.

    TABLE OF CONTENTS

     BUSINESS  
     MARKETING ESSENTIALS

    What Is Social Networking?


    By 

    WILL KENTON

    Updated September 15, 2022

    Reviewed by 
    JULIUS MANSA

    Fact checked by 

    AMANDA JACKSON
    Investopdia / Julie Bang

    What Is Social Networking?


    The term social networking refers to the use of internet-based social media sites to stay
    connected with friends, family, colleagues, or customers. Social networking can have a social
    purpose, a business purpose, or both, through sites like Facebook, Twitter, Instagram, and
    Pinterest.

    Social networking is also a significant opportunity for marketers seeking to engage customers.
    Facebook remains the largest and most popular social network, with 2.91 billion people using the
    platform on a monthly basis, as of Dec. 31, 2021.1 Instagram, Twitter, and Pinterest are among
    the next most popular, according to Statista.2

    KEY TAKEAWAYS

     Social networking is the use of internet-based social media platforms to get and stay connected
    with friends, family, or peers.
     Three of the most popular social networking sites in the U.S. include Facebook, Instagram, and
    Twitter.
     Marketers use social networking to increase brand recognition and encourage brand loyalty.
     Social media can help connect people with businesses for various needs.
     There are disadvantages related to social media, including the spread of misinformation,
    concerns posed by user anonymity, and the high cost of using and maintaining social network
    profiles.
    How Social Networking Works
    Social networking involves the development and maintenance of personal and business
    relationships using technology. This is done through the use of social networking sites, such
    as Facebook, Instagram, and Twitter.

    These sites allow people and corporations to connect with one another so they can develop
    relationships and share information, ideas, and messages.

    For Family and Friends

    Family members and friends can reconnect and remain connected through personal social
    networking sites like Facebook. They can share photos and status updates on everyday or
    important events in their lives. People can also connect with unknown individuals who share the
    same interests, goals, or experiences. Individuals can find each other through groups, lists, and
    the use of hashtags.

    For Marketers

    Social networking is commonly used by marketers to increase brand recognition and encourage


    brand loyalty. Social media marketing helps promote a brand’s voice and content. It can help
    make a company more accessible to new customers and more prominent for existing ones,

    For example, a frequent Twitter user may learn about a company for the first time through a
    news feed and decide to buy a product or service. The more exposed people are to a company’s
    brand, the greater the company's chances of finding and retaining new customers.
    Marketers use social networking to improve conversion rates. Building a following provides
    access to and interaction with new, recent, and longtime customers. Sharing blog posts, images,
    videos, or comments on social media allows followers to react and engage, visit a company’s
    website, and become customers

    You might also like