Reorder and parse author names

Converts author names to "First Last" order and breaks each name into its components. The parser is aware of nobiliary particles (van, von, de, del, da, der, ...) and generational suffixes (Jr, Sr, II, III, IV), and is case-insensitive so it handles bibnets' uppercased entity labels.

Usage

parse_names(
  x,
  format = c("first_last", "last_initials", "last"),
  surname_first = c("auto", "yes", "no")
)

Arguments

x

Character vector of author names, one name per element. NA and empty strings are preserved.

format

Output style for personal names (group/corporate authors, NA, and empty strings are returned unchanged in every style). One of:

"first_last": (default) "Saqr, Mohammed" -> "Mohammed Saqr".
"last_initials": "Saqr, Mohammed" -> "Saqr M."; multiple given names become concatenated initials ("Garcia Marquez G.J."); any suffix is appended ("Smith J. Jr").
"last": surname only, including any particle ("van der Berg", "de la Cruz").

surname_first

How to read comma-less strings (strings with a comma are always "Last, First"). One of:

"auto": (default) surname-first when the trailing token looks like initials — an all-uppercase token of 1-3 letters, the Scopus / bibnets signature ("WANG Y" -> "Y Wang"'s components). Otherwise treated as "First Last". This is the "bibnets takes precedence" bias: native bibnets/Scopus labels parse correctly with no extra arguments, while ordinary mixed-case "First Last" input is never misread.
"yes": force surname-first ("Wang Yong" -> surname Wang, given Yong).
"no": force given-first ("First Last"); comma-less input is returned unchanged.

May also be given as the logical TRUE / FALSE. Inherently ambiguous input (e.g. uppercase "MOHAMMED LI") follows the auto bias toward the bibnets/Scopus convention; pass "no" to override.

Value

A character vector the same length as x, formatted per format. The parsed components are attached as the attribute "parts" (independent of format): a data frame with columns original, first, last, particle, suffix, and type (one of "person", "organization", "empty", "missing"). Casing of the input is preserved; periods are stripped from parsed initials.

Details

Three name conventions are recognised:

"Last, First" (a comma) — always parsed as surname-then-given.
"SURNAME Initials" (no comma, e.g. "WANG Y", "AYALA-ROMERO JA") — the Scopus / bibnets author-label form.
"First Last" (no comma, e.g. "Mohammed Saqr").

Comma-less strings that look like group or corporate authors (e.g. "WHO Collaborating Group") are detected and left untouched, as are NA and empty strings.

This is an optional, standalone utility. No reader or network builder in bibnets calls it; entity labels are matched verbatim unless you choose to apply this function yourself first.

Input shape

parse_names() takes a flat character vector (one name per element) — not a data frame and not a list. bibnets readers store authors as a list-column (each element is a character vector, because a paper has a variable number of authors), so map the function over it rather than passing the column directly:

df$authors <- lapply(df$authors, parse_names, format = "last_initials")

For an ordinary flat character column (or the from / to columns of a bibnets_network), call it directly: parse_names(df$col).

Recommended workflow

Normalise names before building a network, on the reader's authors list-column. Node identity in bibnets is fixed when the bipartite matrix is built (labels are upper-cased and matched verbatim), so two spellings of one author ("Saqr, Mohammed" and "SAQR M") only merge into a single node if they are normalised before author_network() is called:

d <- read_biblio("scopus.csv")
d$authors <- lapply(d$authors, parse_names, format = "last_initials")
net <- author_network(d, type = "collaboration")

Applying to an existing edgelist

You can call parse_names() on the from / to (or source / target) columns of a built network, but it is a per-column, graph-blind relabelling: 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, so distinct authors can collapse onto one label (especially with "last_initials"), and bibnets does not re-aggregate the resulting duplicate edges.

Prefer the pre-build workflow above.

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" where the surname is 1-3 letters (e.g. "MOHAMMED LI"). Suffix-first garbage ("Jr., Sammy Davis") is not specially handled. Use surname_first to force interpretation when you know the source convention.

Examples

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

# Alternative output styles
parse_names("Saqr, Mohammed", format = "last_initials")  # "Saqr M."
#> [1] "Saqr M."
#> attr(,"parts")
#>         original    first last particle suffix   type
#> 1 Saqr, Mohammed Mohammed Saqr     <NA>   <NA> person
parse_names("Saqr, Mohammed", format = "last")            # "Saqr"
#> [1] "Saqr"
#> attr(,"parts")
#>         original    first last particle suffix   type
#> 1 Saqr, Mohammed Mohammed Saqr     <NA>   <NA> person
parse_names("van der Berg, Jan", format = "last_initials") # "van der Berg J."
#> [1] "van der Berg J."
#> attr(,"parts")
#>            original first last particle suffix   type
#> 1 van der Berg, Jan   Jan Berg  van der   <NA> person

x <- parse_names("Saqr, M.")
x
#> [1] "M Saqr"
#> attr(,"parts")
#>   original first last particle suffix   type
#> 1 Saqr, M.     M Saqr     <NA>   <NA> person
attr(x, "parts")
#>   original first last particle suffix   type
#> 1 Saqr, M.     M Saqr     <NA>   <NA> person

# Particles and suffixes
parse_names(c("van der Berg, Jan", "Smith, John, Jr.", "de la Cruz, Ana"))
#> [1] "Jan van der Berg" "John Smith Jr"    "Ana de la Cruz"  
#> 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

# Scopus / bibnets surname-first labels are detected automatically
parse_names(c("WANG Y", "AYALA-ROMERO JA", "VAN DER BERG J"))
#> [1] "Y WANG"          "JA AYALA-ROMERO" "J VAN DER BERG" 
#> 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
#> 3  VAN DER BERG J     J         BERG  VAN DER   <NA> person
parse_names("WANG Y", format = "last_initials")          # "WANG Y."
#> [1] "WANG Y."
#> attr(,"parts")
#>   original first last particle suffix   type
#> 1   WANG Y     Y WANG     <NA>   <NA> person

# Override the auto heuristic when you know the convention
parse_names("Wang Yong", surname_first = "yes")          # "Yong Wang"
#> [1] "Yong Wang"
#> attr(,"parts")
#>    original first last particle suffix   type
#> 1 Wang Yong  Yong Wang     <NA>   <NA> person

# Group authors are detected and left unchanged
parse_names("WHO Collaborating Group")
#> [1] "WHO Collaborating Group"
#> attr(,"parts")
#>                  original first last particle suffix         type
#> 1 WHO Collaborating Group  <NA> <NA>     <NA>   <NA> organization

# Recommended workflow: normalise the authors list-column, then build
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 <- lapply(papers$authors, parse_names,
                         format = "last_initials")
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