Regression Analysis of Lexical and Morpho-Syntactic Properties of Kiezdeutsch (2021)

Abstract: Kiezdeutsch is a variety of German predominantly spoken by teenagers from multi-ethnic urban neighborhoods in casual conversations with their peers. In recent years, the popularity of Kiezdeutsch has increased among young people, independently of their socio-economic origin, and has spread in social media, too. While previous studies have extensively investigated this language variety from a linguistic and qualitative perspective, not much has been done from a quantitative point of view. We perform the first large-scale data-driven analysis of the lexical and morpho-syntactic properties of Kiezdeutsch in comparison with standard German. At the level of results, we confirm predictions of previous qualitative analyses and integrate them with further observations on specific linguistic phenomena such as slang and self-centered speaker attitude. At the methodological level, we provide logistic regression as a framework to perform bottom-up feature selection in order to quantify differences across language varieties.

## introduction over the past 50 years, europe has seen a substantial increase in the number of immigrants and in the diversity of their origin. a direct consequence of this situation is the rise of the so-called "urban youth languages" @xcite : specific linguistic practices used by young people in multiethnic urban areas. one example of urban youth languages is kiezdeutsch ('hood german'), which is a linguistic variety of german spoken primarily by teenagers from multi-ethnic urban neighborhoods in casual conversations with their peers. kiezdeutsch first appeared over 30 years ago and has since then developed systematic linguistic structures that identify it as an independent variety of german @xcite . recent studies have shown that the stylistic elements of kiezdeutsch have spread in the repertoires of many young german speakers without immigrant background @xcite . at the syntactic level, the main differences with standard german are (see examples below): bare noun phrases (1) lacking determiners or (2) lacking prepositions; (3) lack of copula verbs; (4) verb-first declaratives; and (5) subjectverb-object (svo) word order in sentences beginning with an adverb. in previous work, researchers have studied various linguistic aspects of kiezdeutsch focusing on either qualitative analyses @xcite @xcite @xcite @xcite or small-scale quantitative analyses @xcite @xcite . in this work we suggest logistic regression as a general framework to perform bottom-up data-driven feature selection in order to quantify differences across language varieties. we use kiezdeutsch as a test case by comparing against standard german, and we deliberately select simple lexical and morpho-syntactic features that can easily be obtained from standard part-of-speech (pos) taggers and lemmatisers. in this vein, we present three studies: morpho-syntactic variation in terms of part-of-speech unigram distributions (study 1) and in terms of part-of-speech trigram distributions (study 2); and lexical variation in the usage of nouns and verbs (study 3). ## previous work on kiezdeutsch in the mid-1990s the release of two books sparked interest in migrant varieties of german in germany, a collection of semi-fictitious interviews with young men from turkish backgrounds living in berlin @xcite , and a documentation of a turkish youth gang regarding their daily activities @xcite . although these ethnographiccentered analyses were not mainly concerned with language change or variation, they brought to light the notion of groups of young people living in the urban centres of germany who had developed their own language practices as part of their identity. with the turn of the century, more languagecentered studies of this urban vernacular began to appear. in an effort to gain a holistic understanding of kiezdeutsch, @xcite used media text analyses, ethnographic observations and interviews to analyze the speech style of teenagers speaking kiezdeutsch. he then compiled a list of language features on the phonological/phonetic, lexical, and grammatical levels. moreover, androutsopoulos studied the various socio-cultural aspects of kiezdeutsch and their effects on the german language. similarly, @xcite and @xcite identified features of kiezdeutsch through analyses of speech sequences which were then linked to their social interactions and functions as well as their discourses, in order to asses the social and linguistic effects of these features on the german language. their research suggested that kiezdeutsch speakers exhibited a high level of linguistic proficiency and communicative competence, thus contradicting previous views that grammatical simplifications were due to deficiency in language acquisition. these conclusions were in agreement with studies by @xcite who considered kiezdeutsch a multi-ethnolect, and by @xcite who categorized kiezdeutsch as an urban dialect. the introduction of a corpus of spoken kiezdeutsch @xcite led to research across linguistic levels. for example, te velde (2017) investigated phonological form using syntax of verb-second constructions found in the german dialects kiezdeutsch, yiddish, bavarian, cimbrian, and colloquial german. more recently, the effects of english on kiezdeutsch constructions were examined by @xcite who argued that it was necessary to reconsider kiezdeutsch as a native dialect of german, given the role of english as a lingua franca (elf) in urban germany and the effect it has on kiezdeutsch-speaking communities. the above-mentioned studies illustrate the broad spectrum of qualitative evidence and analyses on kiezdeutsch. on the other hand, up to date only a few studies have provided quantitative evidence on kiezdeutsch. one such study was conducted by @xcite who used a gaussian mixture model to explore the durational properties of the particle so in various prosodic positions within utterances of kiezdeutsch speech. the authors supported their findings by predicting distinctions (e.g., utterance-final and phrase-final) from text using punctuation as marker. the work by fuchs and her colleagues examined a single test case of a very specific phonological phenomenon using audio signals as the main source of information. another study by @xcite complemented the work by fuchs and her colleagues by investigating the usage patterns of the particle so using a contingency table and χ 2 tests. the usage-patterns of the same particle were also analyzed quantitatively by @xcite using χ 2 tests. while being close to our studies, the contributions by jannedy and wiese focused on a single test case while we focus on large-scale analyses. moreover, the studies by fuchs et al. and jannedy used a closed-access corpus of speech obtained from interviews with teenagers who speak kiezdeutsch. the work by @xcite combined qualitative and quantitative analyses of several well-established phenomena in kiezdeutsch with the aim of demonstrating the linguistic coherence of this urban vernacular. in their top-down approach, wiese and rehbein started with predefined linguistic patterns and then performed a χ 2 test on the raw corpus frequencies of these patterns. the results pointed to systematic differences between data from the sub-corpus of multi-ethnic speakers and the sub-corpus of mono-ethnic speakers of german. in contrast, our study takes a bottom-up approach and does not define features a priori, but instead allows them to emerge in a data-driven fashion. furthermore, we operate on a large scale and consider all patterns that emerge. to our knowledge, there have been no studies on kiezdeutsch which employ logistic regression models to gather large-scale evidence regarding the various claims and theories in the literature. ## materials in our study, we use two transcribed german spoken corpora: the kidko corpus containing dialogues in kiezdeutsch, and the grain corpus containing radio interviews in standard german. ## logistic regression analyses to identify the most distinctive features in the two corpora we use logistic regression models. in all the models reported below, we predict the categorical variable corpus type (kidko vs. grain) using as predictor the presence/absence of one feature at a time. running a unique model including all the lexicalised features would lead to convergence issues; for this reason, we do not use a bagof-feature classifier approach consistently in all three studies. after fitting the model, we take the z-score corresponding to the predicted variable. in logistic regression, a z-score is the ratio of the coefficient estimate divided by its standard error. the larger the z-score, the less uncertain the prediction is and, consequently, the stronger the difference between the feature in the two corpora. compared to frequency analysis or more traditional estimates like χ 2 , the analysis of the z-scores conveys richer information: the sign of the z-score indicates the direction of the effect if the feature is more predic-tive of the kidko (positive sign) or of the grain corpus (negative sign); moreover, its absolute value is directly related to the level of uncertainty involved in the prediction: larger numbers indicate more reliable predictions. for this reason, we systematically look at the largest positive and negative z-scores in the analyses as the most informative ones. in such way, we filter out features that show a comparable distribution in both corpora and consequently have no discriminative power. finally, by looking at the zscore values it is possible to detect if the probability of selecting one of the two corpora is significantly different from zero (i.e., p-@xmath0.001). in order to reduce type i errors (false positives due to chance), we correct the alpha values by dividing our significance threshold (0.001) by the total number of models we run. ## conclusion the aim of this study was to introduce logistic regression as a general framework to perform bottomup data-driven feature selection in order to quantify differences across language varieties. we applied the framework to kiezdeutsch in comparison to standard german as a test case, which allowed us to identify significant differences at the level of part-of-speech, part-of-speech sequences, as well as lexical choices.