User Modeling in MDE - Data Sheet and Scripts

<p>This replication package contains both the filled out excel template and the used scripts to filter the results at an abstract/title level for ScienceDirect and SpringerLink.&nbsp;<br><br>For ScienceDirect:&nbsp;</p> <ol> <li>Perform the search on the ScienceDirect page and download the results.</li> <li>ScienceDirect proposes a .bib file download. Transform this .bib file into a .ris file using any available online tools for such a conversion.</li> <li>Execute the script 'sciencedirect_filter_script.py' that will ingest a ScienceDirect.ris file and produce a file called 'output_filtered_included.ris' file.</li> </ol> <p>For SpringerLink:</p> <ol> <li>Perform the search on SpringerLink and download the resulting .csv file. and name it SearchResults.csv.</li> <li>The downloaded file does not contain the abstracts, that is why the 'springerlink_abstract_scrape.py' script that will perform a scraping to fetch the abstracts. Execute 'python springerlink_abstract_scrape.py SearchResults.py output.csv'. This will start the scraping and save the results in output.csv. Note that you will need to manually change the name of the columns ['Item Title', 'Authors', 'Publication Year', 'Publication Title', 'URL'] to ['title', 'author', 'year', 'publication', 'link']</li> <li>Perform a manual check if some abstracts are missing. Simply text search the .csv file for 'ABSTRACT NOT FOUND ERROR' and manually enter the missing results.</li> <li>Now use the second script by executing 'python springerlink_filter_script.py' and it will generate a file called 'outputfinalkeyword.ris'</li> </ol> <p>&nbsp;</p> <p>The data extraction excel file contains all the relevant information concerning the data extraction. This includes the reviewed papers, a summary of the numbers, the RQs and metadata.&nbsp;</p>