Help for package ChineseNames

Title:

Chinese Name Database 1930-2008

Version:

2023.8

Date:

2023-08-08

Maintainer:

Han-Wu-Shuang Bao <baohws@foxmail.com>

Description:

A database of Chinese surnames and Chinese given names (1930-2008). This database contains nationwide frequency statistics of 1,806 Chinese surnames and 2,614 Chinese characters used in given names, covering about 1.2 billion Han Chinese population (96.8% of the Han Chinese household-registered population born from 1930 to 2008 and still alive in 2008). This package also contains a function for computing multiple features of Chinese surnames and Chinese given names for scientific research (e.g., name uniqueness, name gender, name valence, and name warmth/competence).

License:

GPL-3

Encoding:

UTF-8

LazyData:

true

URL:

https://psychbruce.github.io/ChineseNames/

BugReports:

https://github.com/psychbruce/ChineseNames/issues

Depends:

R (≥ 4.0.0)

Imports:

bruceR, data.table

Suggests:

babynames, car, dplyr, glue

RoxygenNote:

7.2.3

NeedsCompilation:

Packaged:

2023-08-08 10:20:10 UTC; Bruce

Author:

Han-Wu-Shuang Bao

[aut, cre]

Repository:

CRAN

Date/Publication:

2023-08-08 10:50:02 UTC

ChineseNames: Chinese Name Database 1930-2008

Description

Details

Details are described in https://psychbruce.github.io/ChineseNames/

Citation

Bao, H.-W.-S. (2023). ChineseNames: Chinese Name Database 1930-2008. R package version 2023.8. https://CRAN.R-project.org/package=ChineseNames

Bao, H.-W.-S., Cai, H., Jing, Y., & Wang, J. (2021). Novel evidence for the increasing prevalence of unique names in China: A reply to Ogihara. Frontiers in Psychology, 12, 731244. doi:10.3389/fpsyg.2021.731244

Note

This database does not contain any individual-level information (so it does not leak personal privacy). All data are at the name level or character level. Extremely rare characters are not included.

Source

This database was provided by Beijing Meiming Science and Technology Company (in collaboration) and originally obtained from the National Citizen Identity Information Center (NCIIC) of China in 2008.

Compute multiple features of surnames and given names.

Description

Compute all available name features (indices) based on familyname and givenname. You can either input a data frame with a variable of Chinese full names (and a variable of birth years, if necessary) or just input a vector of full names (and a vector of birth years, if necessary).

Usage 1: Input a single value or a vector of name [and birth, if necessary].
Usage 2: Input a data frame of data and the variable name of var.fullname (or var.surname and/or var.givenname) [and var.birthyear, if necessary].

Caution. Name-character uniqueness (NU) for birth year >= 2010 is estimated by forecasting and thereby may not be accurate.

Usage

compute_name_index(
  data = NULL,
  var.fullname = NULL,
  var.surname = NULL,
  var.givenname = NULL,
  var.birthyear = NULL,
  name = NA,
  birth = NA,
  index = c("NLen", "SNU", "SNI", "NU", "CCU", "NG", "NV", "NW", "NC"),
  NU.approx = TRUE,
  digits = 4,
  return.namechar = TRUE,
  return.all = FALSE
)

Arguments

data

Data frame.

var.fullname

Variable name of Chinese full names (e.g., "name").

var.surname

Variable name of Chinese surnames (e.g., "surname").

var.givenname

Variable name of Chinese given names (e.g., "givenname").

var.birthyear

Variable name of birth year (e.g., "birth").

name

If no data, you can just input a vector of full name(s).

birth

If no data, you can just input a vector of birth year(s).

index

Which indices to compute?

By default, it computes all available name indices:

NLen: full-name length (2~4).
SNU: surname uniqueness (1~6).
SNI: surname initial (1~26).
NU: name-character uniqueness (1~6).
CCU: character-corpus uniqueness (1~6).
NG: name gender (-1~1).
NV: name valence (1~5).
NW: name warmth (1~5).
NC: name competence (1~5).

For details, see https://psychbruce.github.io/ChineseNames/

NU.approx

Whether to approximately compute name-character uniqueness (NU) using the nearest two birth cohorts with relative weights (which would be more precise than just using a single birth cohort). Default is TRUE.

digits

Number of decimal places. Default is 4.

return.namechar

Whether to return separate name characters. Default is TRUE.

return.all

Whether to return all temporary variables in the computation of the final variables. Default is FALSE.

Value

A new data frame (of class data.table) with name indices appended. Full names are split into name0 (surnames, with compound surnames automatically detected), name1, name2, and name3 (given-name characters).

Citation

Bao, H.-W.-S. (2023). ChineseNames: Chinese Name Database 1930-2008. R package version 2023.8. https://CRAN.R-project.org/package=ChineseNames

Note

For details and examples, see https://psychbruce.github.io/ChineseNames/

Examples

## Prepare ##
sn = familyname$surname[1:12]
gn = c(top100name.year$name.all.1960[1:6],
       top100name.year$name.all.2000[1:6],
       top100name.year$name.all.1960[95:100],
       top100name.year$name.all.2000[95:100])
demodata = data.frame(name=paste0(sn, gn),
                      birth=c(1960:1965, 2000:2005,
                              1960:1965, 2000:2005))
demodata

## Compute ##
newdata = compute_name_index(demodata,
                             var.fullname="name",
                             var.birthyear="birth")
newdata

1,806 Chinese surnames and nationwide frequency.

Description

1,806 Chinese surnames and nationwide frequency.

Usage

data(familyname)

Format

A data frame with 7 variables:

surname: surname (in Chinese)
compound: 0 = single surname, 1 = compound surname
initial: initial letter (a-z)
initial.rank: initial order (1-26)
n.1930_2008: total counts in the database
ppm.1930_2008: proportion in population (ppm = parts per million)
surname.uniqueness: surname uniqueness

Details

https://psychbruce.github.io/ChineseNames/

2,614 Chinese characters used in given names and nationwide frequency.

Description

2,614 Chinese characters used in given names and nationwide frequency.

Usage

data(givenname)

Format

A data frame with 25 variables:

character: character used in given names (in Chinese)
pinyin: pinyin (pronunciation)
bihua: number of strokes in a character
n.male: total counts in male
n.female: total counts in female
name.gender: difference in proportions of a character used by male vs. female
n.1930_1959, n.1960_1969, n.1970_1979, n.1980_1989, n.1990_1999, n.2000_2008: total counts in a birth cohort
ppm.1930_1959, ppm.1960_1969, ppm.1970_1979, ppm.1980_1989, ppm.1990_1999, ppm.2000_2008: proportion (parts per million) in a birth cohort
name.ppm: average ppm (parts per million) across all cohorts
name.uniqueness: name-character uniqueness (in naming practices)
corpus.ppm: proportion (parts per million) in contemporary Chinese corpus
corpus.uniqueness: character-corpus uniqueness (in contemporary Chinese corpus)
name.valence: name valence (positivity of character meaning) (based on subjective ratings from 16 raters, ICC = 0.921)
name.warmth: name warmth/morality (based on subjective ratings from 10 raters, ICC = 0.774)
name.competence: name competence/assertiveness (based on subjective ratings from 10 raters, ICC = 0.712)