Here are the steps necessary to calculate a range of indicators for a collection of publications, including the Mean Normalised Log-transformed Citation Score (MNLCS) and the Normalised Proportion Cited (NPC).
- Step 1: Identify the group of publications to be assessed and categorise them by field (e.g., using Scopus or WoS subject categories).
- Step 2: Save the article information (authors, title, journal, publication year) in a standard tab-delimited format in a separate file for each subject category/year combination. First, discard publications that are in small subject/year combinations (e.g., <100 publications). Create tab-delimited files for the each subject/year. There should be one line per publication. Each line should contain the author names in standard format (following Scopus or Web of Science formats would be ideal), the publication year, the article title and the journal name (ignore this for books). The first line of the file should contain header information. Here is an example of the format for journal articles and for books. If your data is in a spreadsheet, it can be saved in this format using the Save As command and selecting the Plain text (tab delimited) format. The filename for each file must contain the subject name and year, and end with -[group].txt, where [group] should be replaced by a name for the collection of articles. The same [group] should be used for files containing publications from the same group. If the files are in Scopus of the Web of Science then choose the tab delimited format in which to save them.
- Step 3: For each retained subject/year combination, a benchmarking sample is needed of articles from the rest of the world. For this, download all articles from the Scopus/WoS (if possible) field/year or a large balanced sample (e.g., the first and last 5000 articles published in the category) for the world reference set. Filter out any large trade or art journals with a high proportion of uncited articles. Name the files using the standard Webometric Analyst naming convention so that each filename contains the subject name and year, and ends with -world.txt. These filenames must exactly match the group filenames, except for replacing -[group].txt with -world.txt. All of the files should be stored within a single folder that does not contain any other files.
- Here is a small artificial example of a complete set of files, with all publications in a single file being from the same field and year, and each group file corresponding to a world file.
- Step 4: Add your indicator data to an extra column of your publication files, if it is not already in them.
- Step 5: There is no step 5.
- Step 6: There is no step 6.
- Step 7: Use Webometric Analyst to calculate MNLCS and NPC and confidence limits for both. For this, start Webometric Analyst, close the Startup Wizard and then select Calculate MNLCS, gMNCS, EMNPC (NPC) and MNPC for a set of tab-delimited files (structured file names) from the Reports menu. Select the folder containing all of the files, when requested. This will create two new files. The file called all_data.txt, contains all of the data extracted from the searches in a format that can be loaded into a stats package or spreadsheet. This is a backup file in case you want to calculate your own indicators. The file called report.txt contains MNLCS, gMNCS, EMNPC (NPC) and MNPC values for each individual file in a long list at the top. Near the end of the file it then reports tables of the combined MNLCS and NPC values for the whole collection. This is the main part of the results. Note that EMNPC is the new name for NPC.
- Step 8: If you want MNLCS, EMNPC (NPC) and MNPC calculated separately for each year, then create new folders, one for each year, and copy all the files from each year into the relevant year folder. Repeat the step above for each year folder.