Lexical Patterns in Adolescents’ Online Writing: The Impact of Age, Gender, and Education

Abstract

<jats:p> This article examines the impact of the sociodemographic profile (including age, gender, and educational track) of Flemish adolescents (aged 13–20) on lexical aspects of their informal online discourse. The focus on lexical and more “traditional,” print-based aspects of literacy is meant to complement previous research on sociolinguistic variation with respect to the use of prototypical features of social media writing. Drawing on a corpus of 434,537 social media posts written by 1,384 teenagers, a variety of lexical features and related parameters is examined, including lexical richness, top favorite words, and word length. The analyses reveal a strong common ground among the adolescents with respect to some features but divergent writing practices by different groups of teenagers with regard to other parameters. Furthermore, this study analyzes both standardized versions of social media messages and the original utterances (including nonstandard markers of online writing). Strikingly, different results emerge with respect to adolescents’ exploitation of more traditional versus digital literacy skills in relation to their sociodemographic profile, especially with respect to sentiment expression (verbal versus typographic/pictorial). The study suggests that the inclusion of nonverbal communicative strategies, for instance in language teaching, might be a pedagogical asset, since these strategies are eagerly adopted by teenagers who show proof of less developed traditional writing skills. </jats:p>

The impact of analogical effects and social factors on the spelling of partially homophonous verb forms in informal social media writing

“…Messages written by adolescents in Grade 3 (17.66 tokens on average) were significantly longer than the ones written by adolescents in Grade 2 (14.54) (t = [1.22 -3.56], p < .05: 85.50%). This relationship between Post length and the social factors Gender and Age was also established by Hilte (2019: 159), which comes as no surprise since the posts that constitute the corpus for the present study were extracted from the corpus of Hilte (2019, see also Hilte et al (2020a) for the social correlates of post length).…”

“…In Surkyn et al (2019) we suggested that the observed effect of gender could also be an effect of post length in disguise. We hypothesized that boys might have a stronger focus on speed, since they were found to produce shorter messages than girls (see also Hilte 2019: 159;Hilte et al 2020a). When time pressure causes extra pressure on working memory resources needed for correct rule application, the error risk increases (Sandra et al 1999).…”

Interlocutors’ Age Impacts Teenagers’ Online Writing Style: Accommodation in Intra- and Intergenerational Online Conversations

“…Furthermore, teenagers’ age impacts more general text features in informal online writing too (e.g., average sentence length–see Hilte et al, 2020a ), but this falls outside the scope of the present study.…”

“…So theory-oriented students do not appear to have a higher conscious awareness, but they may still have a stronger subconscious perception of others’ language use as well as a greater tendency to pattern matching. In addition, in view of the different curricula of the three educational tracks, especially with respect to Dutch language teaching (see Hilte et al, 2020a for an overview), a stronger command of standard Dutch might be expected from theory-oriented students. This may facilitate these students’ accommodation with respect to orality since they may have more control of their standard versus speech-like rendition of Dutch words and phrases.…”

“…Linguistic features belonging to these three maxims will be the focus of the present paper (see Linguistic Variables for an extensive description and illustrations). Still, an important nuance concerning (online) teenage talk is that adolescence is no homogeneous linguistic period with respect to style (content-wise, younger and older teenagers’ online discourse does reveal the same prominent topics; Hilte et al, 2020a ). The so-called “adolescent peak” phenomenon has been attested repeatedly, with non-standard language use and linguistic nonconformity increasing in early adolescence, peaking mid-puberty (around the age of 15–16) and then decreasing as adulthood comes closer ( De Decker and Vandekerckhove, 2017 , 277; Holmes 1992 , 184).…”