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Semantic Network Analysis in Social Sciences

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big data
Big Data Studies
Category=GPS
Category=JMB
Chinese News Coverage
Clustering Coefficient
co-occurrence networks
Communication Sub-disciplines
computational social science
content analysis methods
CSV File
data analysis
data science
discourse structure mapping
eq_bestseller
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
Iranian Nuclear Threat
Israeli Prime Minister Benjamin Netanyahu
Keyword Network
Leading Communication Journals
Link List
Louvain Method
Male Dataset
Netanyahu's Speeches
Netanyahu’s Speeches
network analysis for large text datasets
Phatic Communication
Professional Development
qualitative data analysis
qualitative methods
quantitative methods
Semantic Network Analysis
Sentiment Analysis
social media data
text analysis
text mining techniques
textual analysis
textual network analysis
Tv News Show
Vanden Abeele
West Germany
WhatsApp Groups
Word Embeddings
Yedioth Ahronoth

Product details

  • ISBN 9780367636524
  • Weight: 460g
  • Dimensions: 156 x 234mm
  • Publication Date: 30 Nov 2021
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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Description

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.
About

Elad Segev (PhD, Keele University) is Associate Professor at the Department of Communication, Tel Aviv University. He studies the relationship between information and power, focusing on global information flows, country image, international news, information search, and the digital divide. In his studies he employs text and network analysis techniques.