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Semantic Network Analysis in Social Sciences

List Price: $66.99
SKU:
9780367636524
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  • Product Details

    Author:
    Elad Segev
    Format:
    Paperback
    Pages:
    248
    Publisher:
    Taylor & Francis (November 30, 2021)
    Language:
    English
    ISBN-13:
    9780367636524
    Weight:
    16.25oz
    Dimensions:
    6.125" x 9.1875"
    File:
    TAYLORFRANCIS-TayFran_260213053419714-20260213.xml
    Folder:
    TAYLORFRANCIS
    List Price:
    $66.99
    Case Pack:
    10
    As low as:
    $63.64
    Publisher Identifier:
    P-CRC
    Discount Code:
    H
    Audience:
    College/higher education
    Country of Origin:
    United States
    Pub Discount:
    30
    Imprint:
    Routledge
  • Overview

    Semantic Network Analysis in Social Sciences introduces the fundamentals of semantic network analysis and its applications in the social sciences. Readers learn how to easily transform any given text into a visual network of words co-occurring together, a process that allows mapping the main themes appearing in the text and revealing its main narratives and biases.

    Semantic network analysis is particularly useful today with the increasing volumes of text-based information available. It is one of the developing, cutting-edge methods to organize, identify patterns and structures, and understand the meanings of our information society. The first chapters in this book offer step-by-step guidelines for conducting semantic network analysis, including choosing and preparing the text, selecting desired words, constructing the networks, and interpreting their meanings. Free software tools and code are also presented. The rest of the book displays state-of-the-art studies from around the world that apply this method to explore news, political speeches, social media content, and even to organize interview transcripts and literature reviews.

    Aimed at scholars with no previous knowledge in the field, this book can be used as a main or a supplementary textbook for general courses on research methods or network analysis courses, as well as a starting point to conduct your own content analysis of large texts.