Language and Identity among Intensive Users of Social Media (July 2022)

The study on language and identity among intensive users of social media was conducted by Kantar Public on behalf of the Press and Information Office of the Federal Government. During the survey period 21.07.2022 to 03.08.2022, intensive users of social media aged 16 and over in Germany were asked in online interviews (CAWI) about the following topics: attitudes to non-discriminatory language, evaluation of language and discussion culture in social media, opinions on the use of gender-equitable and non-discriminatory language in general and specifically in social media, and experiences with hate speech on the internet. Respondents were selected through quota sampling from an online access panel (gross initial sample followed by screening for social media use).<br>1. Quoting and screening questions: frequency of use of social networks or social media offerings; social networks or messenger services used at least once a day (Facebook, Instagram, Twitter, YouTube, LinkedIn, Xing, Tumblr, Reddit, Snapchat, TikTok, Twitch, WhatsApp, Telegram); most frequently used social networks or messenger services (ranking).

2. Interest in politics; frequency of seeking information on politics (political informativeness).

3. Language, belonging and language change: self-definition of identity (German language, German nationality, German culture, belonging to my religious community, living in a free and democratic society, job that is fun, friends and/or family I can rely on); definition of German culture (e.g. equal rights for men and women, high value placed on family, freedom, multiculturalism, attachment to home, etc.). ); strength of language change in the last 10 to 20 years; language change all in all to the positive or to the negative; evaluation of language change on the basis of pairs of opposites (more understandable - more incomprehensible, simpler - more complicated, more cultivated - more vulgar, more sophisticated - less sophisticated, more politically correct - more politically incorrect, more varied - more monotonous, more beautiful - less beautiful); Assessment of the quality of political discussions in social networks using pairs of opposites (more respectful - less respectful, more informative - less informative, more emotional - less emotional, more politically correct - less politically correct, more likely to reflect important political debates - hardly reflect important political debates, more interesting - less interesting); frequency of interaction in social networks (liking, sharing and commenting on other posts); frequency of own activities in social networks.

4. Gender-equitable language: awareness of gender-equitable language; connotation of gender-equitable language; attitude towards gender-equitable language in general; importance of gender-equitable language in different situations (in conversations among friends, in conversations at work/university, in professional letters and e-mails, in speeches of politicians, in official information materials of the federal government and ministries, in letters from municipal offices or authorities, in articles in newspapers and magazines, in news programmes on TV and in social media); Added value for equality if the female form is always used in addition to the male form; acceptance of the generic masculine (women, diverse); Agreement with various statements on the use of gender-equal language (if you want to change something about the discrimination of certain groups, you have to start with the language, it disturbs the flow of reading if you always use the masculine and feminine form or words like ´citizens´, it has always been common to use only the masculine form, this should not be changed, the language has to change when society changes, etc.). ); evaluation of different possibilities with regard to gender-equitable language of the federal government; use of gender-equitable language; use of gender-equitable language also in social networks; feedback from others on the use of gender-equitable language in social networks.

5. Discrimination through language: language can discriminate against other people; personally experienced discrimination through language; acceptance of the use of discriminatory language in the following cases: Using words that other people, e.g. black people, perceive as discriminatory; using only the masculine and not the masculine and feminine forms in speeches and official letters.

6. Hate speech: perception of hate comments on social networks; own reactions to hate comments (replied to and criticised offensive or derogatory comments, reported offensive or derogatory comments to platform operators, blocked or unfriended people who posted offensive or derogatory comments, took screenshots and reported offensive or derogatory comments to the police); agreeing with different statements on the evaluation of hate comments (e.g. offensive or derogatory comments on the internet are a big problem, etc.); personal experience with hate comments online in social networks or outside the internet in personal contact; reference of hate comments (e.g. to gender, origin, appearance, etc.); assessment of commitment to prosecute hate comments on the internet (to a sufficient extent, should be prosecuted more or less).

Demography: sex; age; education; federal state; mother tongue (German, other); employment; self-rating social class; household size; number of children under 18 in household; net household income; city size; party sympathy; migration background.

Additionally coded was: respondent ID; split question 14; weighting factors.