# Average Citation and Alternative Indicator Values for Groups of Documents

These instructions explain how to gather citation and alternative indicator data, calculate arithmetic and geometric means and the proportion cited for the data, and (if wanted) calculate world normalised average citation MNLCS and average proportion cited NPC indicators. Jump straight to the instructions.

## Indicators for groups of articles

**Arithmetic mean**: The per document usual average of all the indicator data (e.g., citation counts, Mendeley reader counts, web citation counts) - not really appropriate because indicator data is highly skewed

**Geometric mean**: The per document geometric mean average of all the indicator data (e.g., citation counts, Mendeley reader counts, web citation counts) - better than the arithmetic mean for citation data because of skewing.

**Mean of ln(1+raw data)**: The arithmetic mean after a transformation of ln(1+x) to eliminate skewing - better than the arithmetic mean for citation data because of skewing and just as good as the geometric mean.

**Proportion cited**: The proportion of all documents with at least one positive indicator value (e.g., a citation count of at least 1). This can be more useful than the geometric mean if a very low proportion of the documents are cited because it has narrower confidence intervals.

Here is an example of the report that Webometric Analyst will give you for each set of documents:

File: Biochemistry Molecular Biology Alcohol 2012 Records : 500 Arithmetic mean of raw data : 16.844000 Geometric mean (95%CI) of raw data : 7.991652 (7.036911, 9.059811) Mean (95%CI) of ln(1+raw data) : 2.196297 (2.084045, 2.308548) Proportion (95%CI) non-zero : 0.836000 (0.801005, 0.865871) |

## World normalised indicators for groups of articles

**MNLCS** (Mean Log-transformed Normalised Citation Score) is the average number of log-transformed citations for the group, divided by the average number of log-transformed citations for the corresponding world set. Values higher than 1 indicate that the citation counts for the group tend to be above the world average and values below 1 indicate that citation counts for the group tend to be below the world average. Two confidence intervals are reported for MNLCS but the sample confidence intervals should always be used unless making the assumption that the world file contains a complete set of all the world’s articles from the field and year. Blog post describing MNLCS calculations and MNLCS worked example spreadsheet, including confidence limits.

**EMNPC and MNPC** (Equalised/Mean-based Normalised Proportion Cited) is the proportion of articles cited for the group, divided by the corresponding world proportion of cited articles for the same field and year. Values higher than 1 indicate that the proportion of cited articles for the group is above the world average and values below 1 indicate that the proportion of cited articles for the group is below the world average. These figures can be ignored for the World groups because they are always 1. EMNPC and MNPC worked example spreadsheet, including confidence limits.

Here is an example of the report that Webometric Analyst will give you for a group of documents from the same field and year:

Group file: Spain. In set: Biochemistry Molecular Biology Alcohol 2012 Records : 193 Arithmetic mean : 16.663212 Geometric mean (95%CI) of raw data : 8.162284 (6.598901, 10.047313) Mean (95%CI) of ln(1+raw data) : 2.215095 (2.028004, 2.402187) Proportion non-zero (95%CI) : 0.808290 (0.746954, 0.857593) MNLCS - mean (95%CI) of world normalised ln(1+raw data) [population version] : 1.008559 (0.923374, 1.093744) MNLCS - mean (95%CI) of world normalised ln(1+raw data) [sample version] : 1.008559 (0.911468, 1.110933) NPC - world normalised proportion (95%CI) cited (non-zero): 0.966854 (0.893995, 1.045651) |

And here is an example of a combined report for multiple documents from the same group (Spanish research in this case) spanning different fields and years.

MNLCS calculations for all files. ============================================================== Group N MNLCS L95Sample U95Sample L95Pop U95Pop World 1000 1 0.940734 1.064616 0.956326 1.043673 Spain 475 Field equalised proportion non-zero calculations. ========================================================================== Group N PropNonzero Lower95 Upper95 NPC Lower95 Upper95 world 1000 0.767000 0.739807 0.792149 1.000 0.952902 1.049426 Spain 475 |

## Step by step instructions for gathering data and calculating the indicators

Choose which option path to follow, depending on the indicators to be calculated. If you prefer, try a workshop run through of all these tasks instead.

- For world normalised indicators, follow the
variants of steps, otherwise follow the standard__w__variants of steps. If no variants of steps are specified then follow all.__s__ - For citation indicators, follow the C options and not the M and W options.
- For Mendeley indicators, follow the M options and not the C and W options.
- For Web indicators (patent, PowerPoint, grey literature, web, Wikipedia citations), follow the W options and not the C and M options.

Here are the steps needed to gather data and calculate indicators, with worked examples in most. Please try the worked examples first and then repeat with your own data or queries.

- Step 0CWM
: Decide what type of analysis to conduct and which document sets will be needed.__sw__ - Step 1CWM
: Gather the documents using Scopus or Web of Science, if you do not already have them or convert an existing spreadsheet.__sw__ - Step 2
: Name the files with the Webometric Analyst structured file name format__w__ - Step 3C
: Calculate citation count indicators for individual files or sets of files__s__ - Step 3C
: Calculate world normalised citation count indicators (for multiple fields and/or years)__w__ - Step 4M
: Extract Mendeley reader counts for a set of documents.__sw__ - Step 5M
: Calculate Mendeley reader indicators for individual files or sets of files__s__ - Step 5M
: Calculate world normalised Mendeley reader indicators (for multiple fields and/or years)__w__ - Step 6W
: Sign up to Bing to run automatic web queries.__sw__ - Step 7W
: Make web queries for a set of documents__sw__ - Step 8W
: Run web queries for a set of documents - extra instructions for Wikipedia citation searches, PowerPoint citation searches, and for syllabus mention searches.__sw__ - Step 9W
: Calculate web indicators for individual files or sets of files__s__ - Step 10W
: Calculate world normalised web indicators (for multiple fields and/or years)__w__