Parsing and normalising author names

What `parse_names()` is

parse_names() is an optional, standalone utility for cleaning author name strings. It does two things:

Reorders names to "First Last" (or other styles).
Breaks each name into components (first, last, particle, suffix), returned as the "parts" attribute.

It is not called by any reader or network builder. bibnets matches entity labels verbatim; you opt in to normalisation by calling this function yourself.

parse_names(c("Saqr, Mohammed", "Lopez-Pernas, Sonsoles"))
#> [1] "Mohammed Saqr"         "Sonsoles Lopez-Pernas"
#> attr(,"parts")
#>                 original    first         last particle suffix   type
#> 1         Saqr, Mohammed Mohammed         Saqr     <NA>   <NA> person
#> 2 Lopez-Pernas, Sonsoles Sonsoles Lopez-Pernas     <NA>   <NA> person

The three name conventions

Bibliometric exports use three incompatible conventions. parse_names() recognises all three; the rule is decided per string.

Input	Convention	Detected by
`"Saqr, Mohammed"`	`Last, First`	the comma
`"WANG Y"`	`SURNAME Initials` (Scopus/bibnets)	trailing uppercase 1–3 letter token
`"Mohammed Saqr"`	`First Last`	default for comma-less, non-initial

parse_names(c("Saqr, Mohammed", "WANG Y", "Mohammed Saqr"))
#> [1] "Mohammed Saqr" "Y WANG"        "Mohammed Saqr"
#> attr(,"parts")
#>         original    first last particle suffix   type
#> 1 Saqr, Mohammed Mohammed Saqr     <NA>   <NA> person
#> 2         WANG Y        Y WANG     <NA>   <NA> person
#> 3  Mohammed Saqr Mohammed Saqr     <NA>   <NA> person

A comma always means Last, First. For comma-less strings the surname_first argument controls interpretation:

"auto" (default) — surname-first iff the trailing token looks like initials (all-uppercase, 1–3 letters). This is the bibnets-takes-precedence bias: native bibnets/Scopus labels parse correctly with no extra arguments, and ordinary mixed-case "First Last" is never misread.
"yes" / TRUE — force surname-first.
"no" / FALSE — force given-first (comma-less returned unchanged).

parse_names("Wang Yong", surname_first = "yes")   # force surname-first
#> [1] "Yong Wang"
#> attr(,"parts")
#>    original first last particle suffix   type
#> 1 Wang Yong  Yong Wang     <NA>   <NA> person
parse_names("WANG Y",    surname_first = "no")    # force given-first
#> [1] "WANG Y"
#> attr(,"parts")
#>   original first last particle suffix   type
#> 1   WANG Y  WANG    Y     <NA>   <NA> person

Particles and suffixes are handled, and detection is case-insensitive so it works on bibnets’ upper-cased labels:

parse_names(c("van der Berg, Jan", "Smith, John, Jr.",
              "DE LA CRUZ, ANA", "VAN DER BERG J"))
#> [1] "Jan van der Berg" "John Smith Jr"    "ANA DE LA CRUZ"   "J VAN DER BERG"  
#> attr(,"parts")
#>            original first  last particle suffix   type
#> 1 van der Berg, Jan   Jan  Berg  van der   <NA> person
#> 2  Smith, John, Jr.  John Smith     <NA>     Jr person
#> 3   DE LA CRUZ, ANA   ANA  CRUZ    DE LA   <NA> person
#> 4    VAN DER BERG J     J  BERG  VAN DER   <NA> person

Group / corporate authors, NA, and empty strings are left untouched:

parse_names(c("WHO Collaborating Group", NA, ""))
#> [1] "WHO Collaborating Group" NA                       
#> [3] ""                       
#> attr(,"parts")
#>                  original first last particle suffix         type
#> 1 WHO Collaborating Group  <NA> <NA>     <NA>   <NA> organization
#> 2                    <NA>  <NA> <NA>     <NA>   <NA>      missing
#> 3                          <NA> <NA>     <NA>   <NA>        empty

Output styles: `format`

nm <- c("Saqr, Mohammed", "van der Berg, Jan", "Garcia Marquez, Gabriel Jose")
data.frame(
  first_last    = parse_names(nm),
  last_initials = parse_names(nm, format = "last_initials"),
  last          = parse_names(nm, format = "last")
)
#>                    first_last       last_initials           last
#> 1               Mohammed Saqr             Saqr M.           Saqr
#> 2            Jan van der Berg     van der Berg J.   van der Berg
#> 3 Gabriel Jose Garcia Marquez Garcia Marquez G.J. Garcia Marquez

The `"parts"` attribute

The parsed components ride along on every call, independent of format:

x <- parse_names(c("van der Berg, Jan", "Smith, John, Jr."))
attr(x, "parts")
#>            original first  last particle suffix   type
#> 1 van der Berg, Jan   Jan  Berg  van der   <NA> person
#> 2  Smith, John, Jr.  John Smith     <NA>     Jr person

type is one of "person", "organization", "empty", "missing".

Input shape: vector, not data frame

parse_names() works on one flat character vector. It is not a data-frame function.

bibnets readers store authors as a list-column: each paper has a variable number of authors, so the cell holds a vector, not a single string.

papers <- data.frame(id = c("P1", "P2", "P3"), stringsAsFactors = FALSE)
papers$authors <- list(
  c("Saqr, Mohammed", "Lopez, Ana"),
  c("SAQR M",         "Lopez, Ana"),
  c("Saqr, Mohammed", "Chen, Wei"))
papers$authors
#> [[1]]
#> [1] "Saqr, Mohammed" "Lopez, Ana"    
#> 
#> [[2]]
#> [1] "SAQR M"     "Lopez, Ana"
#> 
#> [[3]]
#> [1] "Saqr, Mohammed" "Chen, Wei"

Map the function over the list-column with lapply():

papers$authors <- lapply(papers$authors, parse_names,
                          format = "last_initials")
papers$authors
#> [[1]]
#> [1] "Saqr M."  "Lopez A."
#> attr(,"parts")
#>         original    first  last particle suffix   type
#> 1 Saqr, Mohammed Mohammed  Saqr     <NA>   <NA> person
#> 2     Lopez, Ana      Ana Lopez     <NA>   <NA> person
#> 
#> [[2]]
#> [1] "SAQR M."  "Lopez A."
#> attr(,"parts")
#>     original first  last particle suffix   type
#> 1     SAQR M     M  SAQR     <NA>   <NA> person
#> 2 Lopez, Ana   Ana Lopez     <NA>   <NA> person
#> 
#> [[3]]
#> [1] "Saqr M." "Chen W."
#> attr(,"parts")
#>         original    first last particle suffix   type
#> 1 Saqr, Mohammed Mohammed Saqr     <NA>   <NA> person
#> 2      Chen, Wei      Wei Chen     <NA>   <NA> person

A flat character column (or a network’s from / to) is called directly, no lapply():

parse_names(c("WANG Y", "AYALA-ROMERO JA"))
#> [1] "Y WANG"          "JA AYALA-ROMERO"
#> attr(,"parts")
#>          original first         last particle suffix   type
#> 1          WANG Y     Y         WANG     <NA>   <NA> person
#> 2 AYALA-ROMERO JA   J A AYALA-ROMERO     <NA>   <NA> person

Recommended workflow: normalise before building

Node identity in bibnets is fixed when the network is built (labels are upper-cased and matched verbatim). Two spellings of one author merge into a single node only if normalised before author_network().

Here "Saqr, Mohammed" and "SAQR M" are the same person written two ways. After normalising they both become SAQR M., so the Saqr–Lopez collaboration is correctly counted as 2:

net <- author_network(papers, type = "collaboration")
net
#> # bibnets network: author_collaboration | 3 nodes · 2 edges | counting: full 
#>    from      to       weight  count
#> 1  LOPEZ A.  SAQR M.       2      2
#> 2  CHEN W.   SAQR M.       1      1

Had we built the network first and called parse_names() on from / to afterwards, the two spellings would already have been counted as two separate nodes — too late to merge by relabelling.

Applying to an existing edgelist (and its hazards)

The network object is a data frame (from, to, weight, count) with an extra bibnets_network class for printing:

class(net)
#> [1] "bibnets_network" "data.frame"
is.data.frame(net)
#> [1] TRUE

You can relabel from / to directly, but parse_names() is graph-blind. Edges, pairing, weight and count are preserved, but:

Apply the same call to both endpoint columns, or the two ends use different labels.
The mapping is many-to-one: distinct authors can collapse onto one label (especially "last_initials"), and bibnets does not re-aggregate the resulting duplicate edges.

net$from <- as.vector(parse_names(net$from, format = "last"))
net$to   <- as.vector(parse_names(net$to,   format = "last"))
net
#> # bibnets network: author_collaboration | 3 nodes · 2 edges | counting: full 
#>    from   to    weight  count
#> 1  LOPEZ  SAQR       2      2
#> 2  CHEN   SAQR       1      1

Use as.vector() when assigning back so the "parts" attribute is not carried on the column.

Limitations

Comma-less names are inherently ambiguous. The auto heuristic is biased toward the bibnets/Scopus surname-first convention and may misread uppercase "GIVEN SURNAME" when the surname is 1–3 letters (e.g. "MOHAMMED LI"). Pass surname_first = "no" to override.
Suffix-first malformed input ("Jr., Sammy Davis") is not specially handled.
It normalises string form, not identity: it will not disambiguate two different people who share a surname and initial.

Summary

parse_names(x) — vector in, vector out, with a "parts" attribute.
lapply(df$authors, parse_names) — for the authors list-column.
Normalise before author_network() for correct node merging.
format = "first_last" / "last_initials" / "last"; surname_first = "auto" / "yes" / "no".

What parse_names() is