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https://github.com/soodoku/meta_ps

Production and Consumption of APSR, BJPS, Perspectives, PS, and World Politics Articles
https://github.com/soodoku/meta_ps

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Production and Consumption of APSR, BJPS, Perspectives, PS, and World Politics Articles

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README 

        
## Trends in Production and Consumption of Political Science Articles



Data are from five prominent political science journals: APSR, BJPS, Perspectives, PS, and World Politics. 



### Table of Contents:



* [Preview of Results](#results)

* [Scraping the (meta) data](#get-the-meta-data)

* [The data and the codebook](#data)

* [Scripts for producing the graphs and graphs](#analyze-the-data)

* **Related:** [Proportion of precise quantitative statements in APSR abstracts](https://github.com/soodoku/quant-discipline)



----



### Some Results



The data show that till well into the 1960s, the average article published in the [APSR](http://journals.cambridge.org/action/displayJournal?jid=PSR) was solo-authored. Today, co-authored papers are the norm.



![No. of authors over time](figs/n_authors_per_article_over_time.png)



Over the past 100 or so years, [article length](figs/article_length.pdf) has shown marked variability. There is a marked see-saw pattern in the average length of the article, but unlike top economics journals we don't see a marked trend towards longer articles. It is very likely, however, that the length of online appendices has grown substantially. 



Number of views an [article](figs/fulltext_views.pdf) or [abstract](figs/abstract_views.pdf) has received follows the familiar power law distribution with most articles receiving very few views. 



----- 



### Get the (Meta) Data



All the data are from journals published by the Cambridge University Press (CUP). CUP has a single publishing platform for all its journals with the link differing only by 'JID'. For instance, to scrape meta data and abstract for all APSR articles from CUP, use [(http://journals.cambridge.org/action/displayBackIssues?jid=PSR](http://journals.cambridge.org/action/displayBackIssues?jid=PSR). The JIDs for various journals are easily found. They can also be scraped from the CUP page listing all the journals that it publishes. 



To scrape the data, use [get_data.py](scripts/get_data.py). The script depends on `urllib2`. To run the script, `python get_data.py`



**Options:**

   * Name of the output file. Specify `FINAL_OUTPUT_FILE` on line 11 of [get_data.py](scripts/get_data.py).

   * Column names. Specify `HEADER` on Line 18 of [get_data.py](scripts/get_data.py).



**Note:** The script allows for interruption. If interrupted, it will restart from where it stopped. And it will append the results to the existing output file.



### Data



  * [APSR](data/apsr_data.csv)  

  * [BJPS](data/bjps_data.csv)  

  * [Perspectives](data/pps_data.csv)  

  * [PS](data/psc_data.csv)  

  * [World Politics](data/wpo_data.csv)  

  

Each row in the csv is a separate article. And the columns are:  

   

   * article.url

   * issue.year

   * issue.volume 

   * issue.date.of.publication

   * issue.pages

   * article.title

   * article.abstract

   * article.pages

   * 10 colums e.g author1, institution1, etc, ...,author1, institution1 

   * article.abstract.views

   * article.full.text.views



### Analyze the Data



* [Recode the data](scripts/meta_apsr.R)

* Article lengths (measured by number of pages) over time. ([Script](scripts/article_length.R), [Graph](figs/n_pages_per_article_over_time.pdf))  

* Number of authors per article over time. ([Script](scripts/n_authors.R), [Graph](figs/n_authors_per_article_over_time.pdf))  

* Number of articles per issue over time. ([Script](scripts/articles_per_issue.R), [Graph](figs/articles_per_issue_over_time.pdf))  

* Number of pages per issue over time. ([Script](scripts/issue_length.R), [Graph](figs/pages_per_issue_over_time.pdf))  

* Distribution of full text views. ([Script](scripts/fulltext_views.R), [Graph](figs/fulltext_views.pdf))  

* Distribution of abstract views. ([Script](scripts/abstract_views.R), [Graph](figs/abstract_views.pdf)) 

* Proportion of Female Authors per article. ([Script](scripts/gender_authors.R), [Graph](figs/gender_authors_per_article_over_time.pdf)) 

* Based on the idea by [titleogy](http://datacolada.org/2013/12/04/titleogy/), Length of title. ([Script](scripts/title_length.R), [Graph](figs/title_len_over_time.pdf)) 



### License

Released under [CC BY 2.0](https://creativecommons.org/licenses/by/2.0/).