EULingDiv

Although the European Union is committed to linguistic diversity by recognizing 24 official EU languages and actively promoting multilingualism, there has not been much effort vested into quantitatively assessing the linguistic diversity of the union. However, two eurobarometer surveys have been conducted that tangentially survey this purpose: one in 2012 and one in 2024. In the surveys, questions are posed pertaining to the native language and first to third other language, which we interpret as corresponding to L1 to L4, thus potentially allowing for more accurate models of linguistic diversity that account for multilingualism. To allow for easier analysis of the data, we have merged and structured the data pertaining to spoken language across the surveys into the dataframe EU_country_speakers_2012_2024.csv. The dataframe is structured in a long format with country-language-year-group-speakers pentuplets. We have not converted the numbers into proportions and derived any formal measures, since there are many analysis-specific aspects necessary to account for, e.g., the weighting given to L1 contra L2, L3, etc. Furthermore, the survey is sample-based, and by summing the L1-speakers of each country, one arrives at the sample size. As such, consideration needs to be made regarding the uncertainty of potential diversity indices derived from the data. While we have added ISO codes to make the dataset more interoperable, one should be wary of the presence of macrolanguages. For example, the survey designates speakers of "Arabic" and "Albanian", but does not specify the varieties such as Tosk or Gheg Albanian. We have kept with this and added the macroidentifyer of "ara" and "sqi" in such cases. The following macrolanguage are in the dataset: ara, sqi, kur, zho, srd, rom, yid. In addition, the sami languages lack a macroidentifier, but the exact variety is not specified in the survey. We therefore used the ISO-code of northern sami, sme, to represent sami language Furthermore, the languages included in the surveys of 2012 and 2024 do not necessarily fully overlap due to hdifferences in design, e.g., what languages were included. The dataset contains the following columns: country_code: 2-letter ISO-3166 code denoting the country that was surveyed. (character) country_name: Commonly used country names corresponding to the country code - does not follow any particular standards. (character) ISO6393: 3-letter ISO639-3 code denoting the language that was surveyed. (character) Language name: Language name used by the original surveys. (character) Speaker_type: Categorical variable denoting if the language is the first (L1), second (L2), third (L3) or fourth (L4) language of the speakers. (character) number_of_speakers: Variable denoting the number of speaker of a variety in a given country according to a given type. (double) year: Denotes which year and survey the data is sourced from (integer) The code developed to construct the dataset can be found at: https://github.com/Eszettfors/EULingDiv ------ v.1.1 fixed an error regarding the L4 speaker numbers in 2024. v.1.2 Fixed a trailing error regarding L4 speaker numbers. Adjusted country codes for Greece and the United Kingdom: EL --> GR; UK --> GB