Software Words
The language of the Twitter user interface is the language that the user chooses to interact with and not necessarily the language that they choose to tweet in. When comparing user interface language with whether location service are enabled or not we find 123 different languages, many of which are in single of double figures, therefore we present only the 20 most frequently occurring user interface choices in Table 5 below. There is a statistically significant association between user interface language and whether location services are enabled both when taking only the top 20 (x 2 = 83, 122df, p<0.001) and all languages (x 2 = 82, 19df, p<0.001) although the latter is undermined by 48.8% of cells having an expected count of less than 5, hence the need to be selective.
8%), closely accompanied by people who interact in the Chinese (24.8%), Korean (26.8%) and German (27.5%). The individuals probably allow the brand new settings make use of the Portuguese software (57.0%) with Indonesian (55.6%), Spanish (51.2%) and you will Turkish (47.9%). You can speculate as to why this type of distinctions occur in family so you’re able to social and you will governmental contexts, but the variations in taste are unmistakeable and you will visible.
The same analysis of the top 20 countries for users who do and do not geotag shows the same top 20 countries (Table 6) and, as above, there is a significant association between the behaviour and language of interface (x 2 = 23, 19df, p<0.001). However, although Russian-language user interface users were the least likely to enable location settings they by no means have the lowest geotagging rate (2.5%). It is Korean interface users that are the least likely to actually geotag their content (0.3%) followed closely by Japanese (0.8%), Arabic (0.9%) and German (1.3%). Those who use the Turkish interface are the most likely to use geotagging (8.8%) then Indonesian (6.3%), Portuguese (5.7%) and Thai (5.2%).
In addition to conjecture over these particular distinctions are present, Tables 5 and you can 6 demonstrate that there clearly was a user software code effect inside play you to shapes behavior in both whether area properties try allowed and you may if or not a user uses geotagging. Screen language is not a good proxy to possess venue very these types of can not be called once the nation level effects, but perhaps there are cultural differences in thinking with the Fb play with and you can privacy for which interface language acts as a beneficial proxy.
User Tweet Vocabulary
The language of individual tweets can be derived using the Language Detection Library for Java . 66 languages were identified in the dataset and the language of the last tweet of 1,681,075 users could not be identified (5.6%). There is a statistically significant association between these 67 languages and whether location services are enabled (x 2 = 1050644.2, 65df, p<0.001) but, as with user interface language, we present the 20 most frequently occurring languages below in Table 7 (x 2 = 1041865.3, 19df, p<0.001).
Given that when examining screen code, profiles just who tweeted for the Russian was basically at least likely to enjoys location services permitted (18.2%) with Ukrainian (22.4%), Korean alt (twenty eight.9%) and Arabic (31.5%) tweeters. Users composing in Portuguese had been the best to have area properties let (58.5%) directly trailed because of the Indonesian (55.8%), the fresh Austronesian words regarding Tagalog (the state title to possess Filipino-54.2%) and you may Thai (51.8%).
We present a similar analysis of the top 20 languages for in Table 8 (using ‘Dataset2′) for users who did and did not use geotagging. Note that the 19 of the top 20 most frequent languages are the same as in Table 7 with Ukrainian being replaced at 20 th position by Slovenian. The tweet language could not be identified for 1,503,269 users (6.3%) and the association is significant when only including the top 20 most frequent languages (x 2 = 26, 19df, p<0.001). As with user interface language in Table 6, the least likely groups to use geotagging are those who tweet in Korean (0.4%), followed by Japanese (0.8%), Arabic (0.9%), Russian and German (both 2.0%). Again, mirroring the results in Table 6, Turkish tweeters are the most likely to geotag (8.3%), then Indonesian (7.0%), Portuguese (5.9%) and Thai (5.6%).