Google Scholar scrape and analysis program
Budget: £20 – £250 GBP
I'm looking to hire a freelancer to develop an automated program that collects and analyzes data from Google Scholar. The program needs to be written in either Python, C++, or JavaScript, and must be able to generate spreadsheet outputs. The program should be manually initiated whenever an analysis is required, as opposed to running on a regular schedule.
This will be a Windows-compatible desktop program to receive as input a Google Scholar search string and output a table of the year-by-year citation history of the top ten most frequently cited documents for each year.
There are two relevant levels of data for a Google Scholar search. The primary level is the initial search results which include each document found by the search, name of the document, number times the document has been cited in other documents, the year of publication, and a link to the secondary level. The secondary level is the "Cites" for each document, which include the name and year of publication of those secondary/citing documents.
The program needs to identify the ten most frequently cited documents in each year for the search string ("Top Documents") - so will need to count the Cites per year for each primary document. Then for each Top Document report the number of citations for each year since it was published (ie before and after the year that qualified them as a Top Author). The output should be a .xlsx spreadsheet (or otherwise Excel import compatible) showing the list of all Top Documents and their number of cites per year.
Deliverables will be a working executable file for the program that will work on Windows 11 Home; source code; and a brief written description of the process.
This will be a Windows-compatible desktop program to receive as input a Google Scholar search string and output a table of the year-by-year citation history of the top ten most frequently cited documents for each year.
There are two relevant levels of data for a Google Scholar search. The primary level is the initial search results which include each document found by the search, name of the document, number times the document has been cited in other documents, the year of publication, and a link to the secondary level. The secondary level is the "Cites" for each document, which include the name and year of publication of those secondary/citing documents.
The program needs to identify the ten most frequently cited documents in each year for the search string ("Top Documents") - so will need to count the Cites per year for each primary document. Then for each Top Document report the number of citations for each year since it was published (ie before and after the year that qualified them as a Top Author). The output should be a .xlsx spreadsheet (or otherwise Excel import compatible) showing the list of all Top Documents and their number of cites per year.
Deliverables will be a working executable file for the program that will work on Windows 11 Home; source code; and a brief written description of the process.