A study of death and demographics, of citation attributes

This study hinges on the analogy between the historical number of citations through time, and the life course of a person. In it I define death and rebirth, and produce basic demographic plots for arbitrary attributes of a citation. This study looks at web of science for sociology in particular.

P( die in next 5 years | alive )

Sleeping beauties

Probability dead by 2010

There are more!

Feel free to explore all the figures included in this, and make your own. I hope this proves helpful!

Reproduce the results

To reproduce these results, or modify them for your own purposes, follow one of the following instructions...

Google's Colaboratory (Cloud)

You can run these algorithms completely free through your browser, thanks to Google.

1. Clone this repo into your own GitHub account.
2. Open Google's Colab environment.
3. From Colab's File menu, choose "Open," and open one of the notebooks in this repository from GitHub. The first cell should automatically install knowknow for you. If it doesn't, run !pip install knowknow-amcgail in the Colab notebook.

Jupyter notebook (Locally)

1. Use GitHub desktop to clone this repository and download it to your own desktop or laptop.
2. Install Python 3 and pip install knowknow-amcgail
3. In the "citation-death" folder, execute jupyter lab.
4. Explore the .ipynb files to see how the analyses were run, and run yourself.
5. Google if you get stuck :) or DM me (@someKindOfAlec)