Skip to content

Experiments and tutorials from the wide field of cultural analytics based on textual and multimodal corpora. Sample use cases range from image retrieval over sentiment analysis to network analysis. Based on Python, JavaScript, and D3.js.

License

Notifications You must be signed in to change notification settings

elektrobohemian/CulturalAnalytics

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

CulturalAnalytics

Experiments and tutorials from the wide field of cultural analytics based on textual and multimodal corpora.

Analyzing Unstructured Data

Superheroes teaser image

In this tutorial you will learn to:

  • web/screen scrape relatively unstructured data from the Wikipedia
  • transform unstructured data into tabular data to facilitate processing with Python
  • create graph data from your data to visualize your data as networks
  • export Python-created data to use it with JavaScript visualization libraries such as D3.js

Would you should already know:

  • a little Python 3
  • some minor HTML
  • some JavaScript if you want to understand the web-based visualization at the end of the tutorial

This notebook comes with a requirements.txt file to facilitate the installation of package dependencies. To install the dependencies, launch the following command from the command line before you start the notebook:

pip3 install -r requirements.txt

Multimodal Analysis and Enrichment of a Library Metadata Corpus

This notebook eventually evolved into a TPDL publication. ATTENTION! The notebook is no longer maintained here. It has been moved to a separate repository.

  • In this tutorial, you will learn to read metadata from an OAI-PMH data provider and how to convert the retrieved data from Dublin Core to a pandas data frame.
  • Furthermore, you will carry out some basic data analysis on your data in order to find out if the data is corrupt or unclean. Based on an example, you will clean some aspects of your data using techniques borrowed from machine learning.
  • Finally, you will visualize data with the help of a network graph.

Sentiment Analysis on the Berlin State Library Catalog and Amazon

Preview In this tutorial, you will learn how to read from a unstructured and structured dataset, create a dataframe from this raw data, and to visualize characteristics from the data in order to find out whether the titles of a research library are truly neutral from a sentiment analysis perspective and how they compare to a sample from books sold by Amazon.

About

Experiments and tutorials from the wide field of cultural analytics based on textual and multimodal corpora. Sample use cases range from image retrieval over sentiment analysis to network analysis. Based on Python, JavaScript, and D3.js.

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published