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As of February 2025, Twitter's advertising reach in South Korea skewed around ** percent in favor of female users, while the remaining ** percent consisted of male users. Twitter has a potential reach of about ** million people in South Korea, which amounts to roughly ** percent of the total population.

In 2021, messaging and video sharing platform Snapchat was more popular than TikTok among Gen Z users in the United States. TikTok counted around 37 million users who were born between 1997 and 2012, while Instagram reported around 33 million users in the same period. Snapchat, which counted 42 million Gen Z users, is projected to reach 49.5 million users in the examined demographic by 2025. Overall, platforms such as Pinterest, Twitter and Reddit had significantly less users amongst this age group.

Market leader Facebook accounted for 59 percent of all social media site visits in Canada in March 2025. Overall, Pinterest ranked second with 15.76 percent of all Canadian social media site visits across desktop and mobile devices. X (formerly Twitter) ranked third, accounting for 9.68 percent.

Description

The MIGR-TWIT Corpus is a multilingual corpus of tweets about the topic of migration in Europe. Within the framework of the collaborative research project OLiNDiNUM (Observatoire LINguistique du DIscours NUMérique, Linguistic Observatory of Online Debate) the MIGR-TWIT Corpus is created with the aim of developing language databases of online debate. Considering the global issue of migration in line with British and French political contexts of last dozen years from 2011 to 2022, the corpus consists of two sub-corpora:

• FR-R-MIGR-TWIT-2011-2022 Corpus for French language data (1 January 2011 - 30 June 2022) and

• UK-R-MIGR-RA-TWIT-2012-2022 Corpus for English language data (1 January 2012 - 5 September 2022)

Using the Twitter API v2 Academic Research, tweets containing at least one occurrence of migration or refugee related words are retrieved automatically from 28 right and far-right political figures and parties. The whole corpus contains 18,233 tweets and 533,198 words.

Scientific reference:

Pietrandrea, P., Battaglia, E. (2022). “Migrants and the EU”. The diachronic construction of ad hoc categories in French far-right discourse. Journal of Pragmatics 192, 139-157.

Blandino, G. (2023). 10 years of public debate on immigration: combining topic modeling and corpus linguistics to examine the British (far-)right discourse on Twitter, MA University of Wolverhampton

Jeon, S. (2025). Le discours numérique sur l'immigration en France entre 2011 et 2022. Une analyse de corpus (Online Discourse on Immigration in France between 2011 and 2022. A Corpus Analysis), PhD Thesis, Université de Lille, France.

Contents

The whole corpus contains two CSV Zip files (tabular format) corresponding to each sub-corpus. The complete corpus is presented in two versions, one version with the tweet identifier (data_id) and the text of the tweet (data_text) as a header (folders named FR-R-MIGR-TWIT-2011-2022_textonly and UK-R-MIGR-RA-TWIT-2012-2022_textonly, respectively composed of 12 and 11 Zip files of every single year), and the other version with all tweet fields information included as a header, such as the posting date (data_created_at), the username (author_name), the number of retweets (data_public_metrics_retweet_count), etc., with two folders named FR-R-MIGR-TWIT-2011-2022_meta and UK-R-MIGR-RA-TWIT-2012-2022_meta. Detailed information for each sub-corpus is illustrated below.

1. FR-R-MIGR-TWIT-2011-2022

• Created at: 2022-08-08

• Language: FR

• Coverage: 16 user accounts; 11,761 tweets; 358,491 words

• Time of data collection: start=2011-01-01; end=2022-06-30

• Keywords: words derived from a latin root “migr” of migrare

• Corpus composition:

	Political figure/party	Username	Tweets	Year concerned
1	Michel Barnier	@MichelBarnier	31	2017-22
2	Valérie Pécresse	@vpecresse	81	2017-22
3	Rassemblement National	@RNational_off	3,347	2017-22
4	Nicolas Dupont-aignan	@dupontaignan	663	2011-22
5	Éric Ciotti	@ECiotti	1,007	2012-22
6	Christian Estrosi	@cestrosi	137	2011-22
7	Marine Le Pen	@MLP_officiel	1,650	2011-22
8	Valérie Boyer	@valerieboyer13	837	2012-22
9	Florian Philippot	@f_philippot	485	2012-22
10	Xavier Bertrand	@xavierbertrand	70	2017-22
11	Marion Maréchal	@MarionMarechal	479	2012-17,19-22
12	Philippe Meunier	@Meunier_Ph	245	2013-22
13	Jordan Bardella	@J_Bardella	1,095	2013-22
14	Nicolas Bay	@NicolasBay_	1,260	2017-22
15	Emmanuel Macron	@EmmanuelMacron	72	2017-22
16	Éric Zemmour	@ZemmourEric	302	2019-22
17	Jean Messiha*	Banned from Twitter (since July 2021)	-	-

• Political figures and parties of table above are listed in chronological order according to the dates on which they posted their first tweet.

• *Before the launching of Twitter API v2 Academic Research, migr-tweets were collected from the database of Europresse.com including 1,453 tweets of Jean Messiha as part of the reference study (Pietrandrea & Battaglia 2022). However, the Twitter account in question has been permanently banned since July 2021. For our data collection using the Twitter API started in September 2021, we could not access this account. Therefore, we decided not to include his tweets in the FR-R-MIGR-TWIT-2011-2022 for the sake of consistency with the rest of twitter data that are automatically retrieved.

• The sub-corpus FR-R-MIGR-TWIT-2017-2022 is developed, annotated and analyzed as part of a doctoral thesis in progress (Jeon, 2025) with the aim of studying the semantic construction of migr-lexicon over the period between 2011 and 2022.

2. UK-R-MIGR-RA-TWIT-2012-2022

• Created at: 2022-09-06

• Language: EN

• Coverage: 12 user accounts; 6,472 tweets; 174,707 words

• Time of data collection: start=2012-01-01; end=2022-09-05

• Keywords: words derived from a latin root “migr” of migrare in addition to the keywords “refugee(s)” and “asylum”.

• Corpus composition:

	Political figure/party	Username	Tweets	Year concerned
1	David Cameron	@David_Cameron	32	2012-22
2	Amber Rudd	@AmberRuddUK	29	2012-22
3	Sajid Javid	@sajidjavid	84	2012-22
4	Boris johnson	@BorisJohnson	80	2015-22
5	Priti Patel	@pritipatel	304	2012-22
6	UK Home Office	@ukhomeoffice	909	2012-22
7	Nigel Farage	@Nigel_Farage	1,010	2012-22
8	Richard Tice	@TiceRichard	180	2013-22
9	UKIP	@UKIP	2,746	2012-22
10	Neil Hamilton	@NeilUKIP	252	2013-22
11	Nick Griffin	@NickGriffinBU	542	2012-22
12	Robin Tilbrook	@RobinTilbrook	304	2012-22

• 2 out of 12 accounts are official accounts belonging to the” UK Home Office” department and the “UKIP” (United Kingdom Independence Party) party. 10 out of 12 accounts are political figures’ accounts.

• The corpus UK-R-MIGR-RA-TWIT-2012-2022 will be exploited for the following master’s thesis: Blandino, G. (2023). 10 years of public debate on immigration: combining topic modeling and corpus linguistics to examine the British (far-)right discourse on Twitter, MA University of Wolverhampton.