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Home / Computers - Artificial Intelligence (AI)

Doing Computational Social Science A Practical Introduction 1st Edition John Mclevey

$50.00 Original price was: $50.00.$25.00Current price is: $25.00.

Doing Computational Social Science A Practical Introduction 1st Edition John Mclevey Digital Instant Download

 

Author(s): John McLevey
ISBN(s): 9781526468192, 1526468190, 2021937242
Edition: 1
File Details: PDF, 13.19 MB
Year: 2022
Language: English
SKU: EB-47199482 Category: Computers - Artificial Intelligence (AI) Tags: 1526468190, 2021937242, 9781526468192, Computational Social Science, John McLevey
  • Description

Doing Computational Social Science A Practical Introduction 1st Edition John Mclevey – Ebook Instant Download/Delivery ISBN(s): 9781526468192,1526468190,2021937242

Product details:

• ISBN 10:1526468190, 2021937242
• ISBN 13:9781526468192
• Author(s): John McLevey

Computational approaches offer exciting opportunities for us to do social science differently. This beginner’s guide discusses a range of computational methods and how to use them to study the problems and questions you want to research. It assumes no knowledge of programming, offering step-by-step guidance for coding in Python and drawing on examples of real data analysis to demonstrate how you can apply each approach in any discipline. The book also: Considers important principles of social scientific computing, including transparency, accountability and reproducibility. Understands the realities of completing research projects and offers advice for dealing with issues such as messy or incomplete data and systematic biases. Empowers you to learn at your own pace, with online resources including screencast tutorials and datasets that enable you to practice your skills and get up to speed. For anyone who wants to use computational methods to conduct a social science research project, this book equips you with the skills, good habits and best working practices to do rigorous, high quality work.

Table contents:

  1. Introduction: Learning to Do Computational Social Science
  2. Part I Foundations
  3. Part II Fundamentals of Text Analysis
  4. Part III Fundamentals of Network Analysis
  5. Part IV Research Ethics and Machine Learning
  6. Part V Bayesian Data Analysis and Generative Modelling with Probabilistic Programming
  7. Part VI Probabilistic Programming and Bayesian Latent Variable Models for Structured, Relational, and Text Data
  8. Part VII Embeddings, Transformer Models, and Named Entity Recognition

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