Title: Many Data on State and State-Like Actors in the International System
Version: 1.0.2
Date: 2025-10-08
Description: Comprehensively identifying states and state-like actors is difficult. This package provides data on states and state-like entities in the international system across time. The package combines and cross-references several existing datasets consistent with the aims and functions of the manydata package. It also includes functions for identifying state references in text, and for generating fictional state names.
URL: https://globalgov.github.io/manystates/
BugReports: https://github.com/globalgov/manystates/issues
LazyData: true
License: CC BY 4.0
Depends: R (≥ 3.5.0), manydata
Imports: knitr, purrr, stringi
Suggests: pointblank, messydates, testthat (≥ 3.0.0), rmarkdown
Encoding: UTF-8
RoxygenNote: 7.3.3
Config/Needs/check: covr, lintr, spelling
Config/Needs/website: pkgdown
Config/testthat/parallel: true
Config/testthat/edition: 3
Config/testthat/start-first: code_states
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-10-08 15:05:38 UTC; hollway
Author: James Hollway ORCID iD [cre, aut, ctb] (IHEID), Bernhard Bieri ORCID iD [ctb] (IHEID), Mylan Evrard ORCID iD [ctb] (IHEID), Esther Peev ORCID iD [ctb] (IHEID), Henrique Sposito ORCID iD [ctb] (IHEID), Jael Tan ORCID iD [ctb] (IHEID)
Maintainer: James Hollway <james.hollway@graduateinstitute.ch>
Repository: CRAN
Date/Publication: 2025-10-14 17:50:02 UTC

manystates: Many Data on State and State-Like Actors in the International System

Description

Comprehensively identifying states and state-like actors is difficult. This package provides data on states and state-like entities in the international system across time. The package combines and cross-references several existing datasets consistent with the aims and functions of the manydata package. It also includes functions for identifying state references in text, and for generating fictional state names.

Author(s)

Maintainer: James Hollway james.hollway@graduateinstitute.ch (ORCID) (IHEID) [contributor]

Other contributors:

See Also

Useful links:

Code stateIDs from text

Description

This function allows for contemporary and historical countries or states to be identified in text. It uses a regular expression (regex) to search for a number of common names and alternative spellings for each entity. The function returns either the three-letter abbreviation (an extended version of ISO-3166 alpha-3), or the name of the state. The function can also return multiple matches, where more than one country is mentioned in the text. Currently, the function can identify 500 entities. Updates, bug reports, and suggestions welcome.

Usage

code_states(text, code = TRUE, max_count = 1)

Arguments

text

A vector of text to search for country names within.

code

Logical whether the function should return the three-letter abbreviation (an extended version of ISO-3166 alpha-3), or the name of the state. For the complete list of entities and their search terms, run the function without an argument (i.e. code_states()). Updates and suggestions welcome.

max_count

Integer how many countries to search for in each element of the vector. Where more than one country is matched, the countries are returned as a set, i.e. in the format "{AUS,NZL}". By default max_count = 1, which will just return the first match.

Value

A character vector of the same length as text, with either the three-letter abbreviation (an extended version of ISO-3166 alpha-3), or the name of the state, or NA where no match was found. If max_count > 1, multiple matches are returned as a set, i.e. in the format "{AUS,NZL}". If the function is run without an argument, it returns a data frame with the complete list of entities and their search terms.

Examples

code_states(c("I went to England",
  "I come from Venezuela",
  "Did you know there was a Lunda Empire?",
  "I like both Australia and New Zealand"))
code_states(c("I went to England",
  "I come from Venezuela",
  "Did you know there was a Lunda Empire?",
  "I like both Australia and New Zealand"), max_count = 2)

Generate fictional country names

Description

This function generates a vector of fictional country names. While the generated names are designed to resemble real country names, the results will not match (at least not exactly) country names from the library provided. Please note that the function is still experimental.

The names are generated using a Markov chain approach based on syllable patterns found in a library of real country names. The function generate_states() uses the syllabise_states() function to split existing country names into syllable-like units, providing special attention to common patterns in country names such as "land", "stan", "burg", and others. A transition matrix is then built from these syllable units, allowing for the generation of new names that mimic the structure and length of real country names. Checks are included to ensure that the generated names are unique, do not match any existing country names, and avoid certain uncommon patterns such as ending on a preposition.

If no library of country names is provided, the function defaults to using a comprehensive list of country names from the {manystates} package. However, users can supply their own list of country names to customize the generation process.

This function can be useful for creating fictional datasets for testing, illustrative, or pedagogical purposes. For example, it can be used in classroom exercises that rely on invented country names, such as in-class simulations of international relations or negotiation, role-playing scenarios, or mock data analysis tasks. Using fictional country names helps avoid any unintended bias or preconceptions associated with real countries. Or they can be used in creative writing or game design. The names might inspire fictional settings or entities in stories, games, or other creative works. Each name could inspire a unique culture, conflict, or mythology. Writers could use them to kickstart short stories, while game designers might build entire maps or quests around them.

Usage

generate_states(n = 10, countries = NULL)

syllabise_states(word)

syllabize_states(word)

Arguments

n

Integer number of country names to generate from a library of fictional country names. Default is 10.

countries

Optional string vector of country names to use as a library for generating fictional names.

word

One or more words (character vector) to split into syllable-like units.

Value

String vector of fictional country names

Examples

  generate_states(12)
  syllabise_states("Afghanistan")
  syllabise_states("Saint Pierre and Miquelon")

Objects exported from other packages

Description

These objects are imported from other packages. Follow the links below to see their documentation.

manydata

consolidate

States datacube

Description

The manystates::states datacube is a list containing 3 datasets: ISD, GW, and GGO. It is a work-in-progress, so please let us know if you have any comments or suggestions.

Usage

states

Format

ISD:

A dataset with 499 observations and 36 variables: stateID, StateName, Begin, End, StateNameAlt, Latitude, Longitude, StartType, EndType, cowID, cowNR, ISD_Category, Region, Start_Am, EStart_Am, Declare, DecDate, Population, ..., VioEnd, and VioEnd_Am.

HUGGO:

A dataset with observations and variables: .

GW:

A dataset with 216 observations and 7 variables: stateID, StateName, Begin, End, StateNameAlt, cowID, and cowNR.

For more information and references to each of the datasets used, please use the manydata::call_sources() and manydata::compare_dimensions() functions.

Details

#> $ISD
#> ---------------------------------------------------------
#> |   Variable   |  Class  |  Obs  |  Missing  |  Miss %  |
#> ---------------------------------------------------------
#> |stateID       |character|    499|          0|         0|
#> |StateName     |character|    499|          0|         0|
#> |Begin         |mdate    |    282|        217|     43.49|
#> |End           |mdate    |    499|          0|         0|
#> |StateNameAlt  |character|    210|        289|     57.92|
#> |Latitude      |character|    343|        156|     31.26|
#> |Longitude     |character|    343|        156|     31.26|
#> |StartType     |numeric  |    337|        162|     32.46|
#> |EndType       |numeric  |    296|        203|     40.68|
#> |cowID         |character|    499|          0|         0|
#> |cowNR         |numeric  |    499|          0|         0|
#> |ISD_Category  |numeric  |    497|          2|       0.4|
#> |Region        |numeric  |    499|          0|         0|
#> |Start_Am      |numeric  |    499|          0|         0|
#> |EStart_Am     |numeric  |    232|        267|     53.51|
#> |Declare       |numeric  |    315|        184|     36.87|
#> |DecDate       |character|     72|        427|     85.57|
#> |Population    |character|    319|        180|     36.07|
#> |PopDate       |numeric  |    316|        183|     36.67|
#> |PopAm         |numeric  |    339|        160|     32.06|
#> |PopulationHigh|numeric  |    139|        360|     72.14|
#> |PopulationLow |numeric  |    108|        391|     78.36|
#> |StartType_Am  |numeric  |    339|        160|     32.06|
#> |StartSettle   |numeric  |    320|        179|     35.87|
#> |End_Am        |numeric  |    499|          0|         0|
#> |EndType_Am    |numeric  |    294|        205|     41.08|
#> |EndSettle     |numeric  |    282|        217|     43.49|
#> |Sovereignty_Am|numeric  |    499|          0|         0|
#> |EuroDip       |numeric  |    331|        168|     33.67|
#> |Borders       |numeric  |    332|        167|     33.47|
#> |Borders_Am    |numeric  |    342|        157|     31.46|
#> |Capital       |character|    284|        215|     43.09|
#> |VioStart      |numeric  |    318|        181|     36.27|
#> |VioStart_Am   |numeric  |    327|        172|     34.47|
#> |VioEnd        |numeric  |    292|        207|     41.48|
#> |VioEnd_Am     |numeric  |    297|        202|     40.48|
#> ---------------------------------------------------------
#> 
#> 
#> $GW
#> -------------------------------------------------------
#> |  Variable  |  Class  |  Obs  |  Missing  |  Miss %  |
#> -------------------------------------------------------
#> |stateID     |character|    216|          0|         0|
#> |StateName   |character|    216|          0|         0|
#> |Begin       |mdate    |    216|          0|         0|
#> |End         |mdate    |    216|          0|         0|
#> |StateNameAlt|character|     18|        198|     91.67|
#> |cowID       |character|    216|          0|         0|
#> |cowNR       |character|    216|          0|         0|
#> -------------------------------------------------------
#> 
#> 
#> $GGO
#> -------------------------------------------------------
#> |  Variable  |  Class  |  Obs  |  Missing  |  Miss %  |
#> -------------------------------------------------------
#> |stateID     |character|    409|          0|         0|
#> |StateName   |character|    409|          0|         0|
#> |Capital     |character|    409|          0|         0|
#> |Begin       |mdate    |    409|          0|         0|
#> |End         |mdate    |    409|          0|         0|
#> |Latitude    |numeric  |    409|          0|         0|
#> |Longitude   |numeric  |    409|          0|         0|
#> |Region      |character|    409|          0|         0|
#> |StateNameAlt|character|     61|        348|     85.09|
#> |CapitalAlt  |character|      7|        402|     98.29|
#> |Coder       |character|    409|          0|         0|
#> |Comments    |character|     72|        337|      82.4|
#> |Source      |character|    136|        273|     66.75|
#> -------------------------------------------------------

Mapping

GGO GW ISD
stateID
Begin Start Start
End Finish Finish
StateName Name of State State.Name
cowID Cow ID COW.ID
cowNR Cow NR. COW.Nr

Source