Jupyter Notebooks

King’s College London has developed complete stories around Jupyter Notebooks that form easy recipes for reproducible methods in social data science. Jupyter (http://jupyter.org/) is a web-based computing environment, mostly, but not exclusively based on Python. Content is divided between a number of cells, which may contain code, visualisations and maps, interactive UI elements or rich HTML content.

On top of this foundation, the notebooks add a document-based workflow. Notebook documents contain live code, descriptive text, mathematical equations, interactive user-interface components, images, videos, and arbitrary HTML.

King’s College London has used notebooks in the development of an Apache Spark teaching and experimentation environment, wrapping Apache Spark in an experimental containerised web application that allows users to participate in ad-hoc clusters via Jupyter and produced corresponding multimedia guides.

There are five main topics around which Jupyter Notebooks are organised. Within each main topic, users can find specific exercises, as detailed below. To launch the exercises, follow the .HTML printout within each exercise folder.

Historical Cultures - Analysing Shakespeare - Create Corpus Visualisations - Hate Speech Detection - Getting Started with Quanteda - An introduction to Tidy Text

Prediction Modelling - Linear Regression Prediction - Predicting and Modelling: Neural Networks - Collaborative Filtering Recommender System

Social and Cultural Communities - R Markdown: Notebooks With R 1. Votes in the United Nations General Assembly dataset 2. Collaboration Networks in the United States Congress

Social Sensing - API 1. Facebook 2. Twitter Streaming API 3. Whatsapp - Graphs 1. Eighteenth Century beta of PRISM

Visual Arts - Advanced R Visualisations - Interactive R Visualisations

The multimedia guides are built around Ananke. Ananke is a containerized web application wrapper that allows complete novices to experiment with ad-hoc Apache Spark clusters without access to commercial cloud services.

Ananke Guide Ananke Video Demo

The author did not intend to violate any copyright on figures or content. In case you are the legal owner of any copyrighted content, please contact info@sobigdata.eu and we will immediately remove it

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  • Historical Cultures RepositoryZIP

    Contains exercises in Historical Cultures. To launch the exercises follow...

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  • Prediction Modelling RepositoryZIP

    Contains exercises in Prediction Modelling. To launch the exercises follow...

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  • Social and Cultural Communities RepositoryZIP

    Contains exercises in Social and Cultural Communities. To launch the...

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  • Social Sensing RepositoryZIP

    Contains exercises in Social Sensing. To launch the exercises follow the...

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  • Visual Arts RepositoryZIP

    Contains exercises in Visual Arts. To launch the exercises follow the .HTML...

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  • Ananke GuideZIP

    Ananke Ananke is a containerized web appliction wrapper that allows complete...

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  • Ananke Guide Videomp4

    An early video of Ananke in action

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Additional Info
Field Value
Availability On-Site
Course Interactive Teaching and Experimentation Environment
Keywords Jupyter
Keywords Apache Spark
Keywords R
Keywords Datasets
Keywords Prediction Modelling
Keywords Notebooks with R
Keywords Social Sensing
Keywords Facebook
Keywords Twitter
Keywords Whatsapp
Keywords API
Keywords R Visualisation
Keywords Ananke
Length 5 groups of exercises and Ananke guide
Lesson number 5
Prerequisites Jupyter (http://jupyter.org/) web-based computing environment
Provider Institution King's College London
Target users Social Scientists
Target users PhD Students
Target users Other
Thematic Cluster Text and Social Media Mining [TSMM]
Thematic Cluster Social Network Analysis [SNA]
Thematic Cluster Visual Analytics [VA]
Thematic Cluster Social Data [SD]
Training material typology Other
system:type TrainingMaterial
Management Info
Field Value
Author BRAGHIERI MARCO
Maintainer BRAGHIERI MARCO
Version 1
Last Updated 8 October 2021, 13:09 (CEST)
Created 29 June 2018, 11:35 (CEST)