Non-standard Language Research Articles

Linguistic creativity of the modern gift marketing (based on alcoholic products)

This article describes linguistic creativity in modern gift marketing. The study analyzes the verbal design of alcoholic products’ packaging, which contains creative texts aimed at the mass consumer – a modern linguistic personality, for whom non-standard language solutions have acquired particular value. The author connects the change in the linguistic design of product packaging with the development of mass linguistic creativity, which extends to various types of discourse, including the gift discourse analyzed by the author. The article proves that the creativity of texts on gift alcoholic products is achieved by various linguistic means: violation of language norms, non-standard linguistic combinations, the use of language games that create unpredictability of meanings. Particular attention is paid to the functional aspect of linguistic creativity (attracting consumers’ attention, creating a positive brand image, promoting a product), as well as the axiological component of the analyzed texts. The article concludes that the linguistic design of a product is an effective tool for its promotion, while marketing communication in general and gift marketing communication in particular, reflect the axiological parameters of modern society, for which alcohol products act as an integral attribute of any festive event and/or a desired gift.

The Use of Artificial Intelligence (AI) among International Class Program Students and Its Implication in Their Learning

Artificial Intelligence (AI) is a technology that enables computers to mimic human intellectual abilities, such as learning from experience, identifying patterns, making decisions, and completing complex tasks. AI is currently a popular topic in the field of education, where it can assist teachers in tasks like creating lesson plans, assessing learning outcomes, and providing support to students. AI can also benefit learners by improving their academic performance, making learning more interesting and interactive. AI also believed as a tool for mastering several foreign languages. One of the programs at universities that required students to master a single foreign language is International Class Program (ICP). AI could have an impact in improving academic performance of ICP students. By the case, this study aims to explore the use of AI among International Class Program (ICP) students and its implications for their learning. A survey was conducted among 46 ICP students from seven different majors in the Faculty of Tarbiya and Teacher Training, Maulana Malik Ibrahim State Islamic University of Malang. The results showed that AI is mostly used by ICP students for searching for translations, looking for inspiration, and finding answers. The use of AI has implications for ICP students, such as the lack of mastery of foreign languages. However, AI can also help students master foreign languages quickly, easily, and efficiently. AI can also help students do assignments, find ideas, and create designs or discussions. The information provided by AI tends to be more concise, easy to understand, and informative. The advantages of using AI include helping students find answers efficiently, making it easier for students to find additional information, being practical, growing student inspiration, imagination and creativity, helping students develop a better understanding of technology, assisting in developing designs or discussions, and helping translate accurately. The disadvantages of using AI include dependence, making students lazy, providing inaccurate information, eliminating students' critical thinking, reducing students' literacy, and using non-standard language. In conclusion, AI has both advantages and disadvantages in education. While AI can help students learn more efficiently and effectively, it can also make students lazy and dependent on technology. Therefore, it is essential to use AI wisely and not abuse it in education.

Exploring native language interference of Chinese learners in acquisition of English as a second language on cases in composition of college level students

Under the dominating phenomenon of mandatory English learning among most of Chinese university, students are commonly criticized unnatural Chinglish in their compositions. Thus, it has been a widely studied topics to discover the nature of first language influence on foreign or second language learning. This study investigates the impact of native language interference on the English writing proficiency of Chinese college students. By examining a large body of student papers collected at a corpus created and maintained by Beijing Foreign Studies University, the study aims to identify common grammatical errors and non-standard language that arise when Chinese students switch to English. Another element of the study that tries to identify and illustrate Chinese students' mental processes while they write in English is the semi-structured interview. Observation and analysis reveal that interference from the original tongue often manifests as errors in sentence construction, misuse of articles and agreements, and excessive use of personal pronouns as subjects. This leads to descriptive inappropriate language usage and prescriptive grammar errors in composition. The study emphasizes the necessity for focused pedagogical approaches to deal with these issues, with the ultimate goal of improving English as Second Language (ESL) instruction techniques and raising Chinese learners' confidence and language competency.

Analisis Kesalahan Berbahasa dalam Pidato Presiden Jokowi di Apel Kader Partai Gerindra

This study aims to analyze language errors in President Jokowi's speech at the Gerindra Party Cadre Assembly. Using a qualitative descriptive method, the research examines language use from phonological, morphological, syntactic, and semantic aspects. The data source is a speech video uploaded by the Metro TV YouTube account. Data collection used observation methods with note-taking techniques. The research findings reveal various language errors, including phoneme errors, use of non-standard words, pronunciation mistakes, morphological errors in prefix, suffix, and confix usage, as well as syntactic and semantic errors. Nevertheless, the speech remains comprehensible, demonstrating relatively good communication skills.

신규 표준어의 단어화에 관한 소고 - 2023년 선정 대상을 중심으로

This paper focuses on the phenomenon of wordization in the headwords of the Standard Dictionary and Woorimalsaem dictionaries, as observed in the new standard words selected in 2023, and explores several related questions. First, by comparing the wordized standard words with related vocabulary entries in the dictionary, the study seeks to explore the criteria for determining wordization. Although the study began with an interest in the wordization of new standard words, the discussion was expanded to broader topics, such as the clear distinction between normative grammar (or dictionary) and academic grammar (descriptive grammar and theoretical grammar), as well as the researcher’s attitude towards these distinctions. It is important to clearly recognize the layers of normative grammar and academic grammar, and to carefully examine and utilize the relevant materials according to each level. Particularly, research reports that describe non-standard words, such as neologisms, may be the result of internal guidelines followed by specific researchers or research teams. Since they do not belong to rigorously managed normative grammar, more precise verification is required in academic grammar studies.

Analisis Kesalahan Berbahasa pada Teks Eksplanasi Karangan Siswa Kelas XI MA Hasyim Asy’ari Jogoroto Tahun Pelajaran 2024/2025

This study aims to examine Indonesian language errors in the explanatory text written by class XI students of MA Hasyim Asy'ari Jogoroto in the 2024/2025 academic year. The focus of the research, namely analyzing Indonesian language errors in the fields of phonology, morophology, syntax, and semantics This research uses descriptive qualitative research methods. The data source used is the explanatory text written by students. The research subjects were students of class XI IIS 1 MA Hasyim Asy'ari, Jogoroto. The data collection technique in the research is documentation technique. The data analysis technique in the research consists of; (1) data reduction, (2) data presentation, and (3) verification and conclusion. The results found consisted of 25 Indonesian language errors including, five phonological errors, 13 morphological errors, five syntactic errors, and two semantic errors. Phonological errors consisted of two capital letters, two punctuation marks, and one phoneme omission. Errors in morphology consist of five nonstandard word writings, two word merging errors, one non-yielding affixation writing, and five affixation writing errors. Syntax errors consisted of two redundant word usage three inappropriate diction choices, and semantic errors consisted of two findings.

(Un-)persönliches Schreiben in der Wissenschaftssprache? Eine vergleichende quantitative Studie zu deutschen und polnischen Doktorarbeiten aus der Germanistik

This paper deals with agent demotion and self reference in German as an academic language used by non-native speakers. It examines two comparative corpora consisting of German language dissertations written by L1 speakers from Germany and Austria and L2 speakers from Poland. Significant differences between the two groups are detected regarding the use of different types of agent demotion. These differences may be explained based on the different linguistic and cultural backgrounds of the authors. To complement these statistical findings, the paper also examines some forms of non-standard language use by the L2 speakers that may be traced to Polish influence. A comparison with two previous studies with bachelor and master theses shows that rare constructions increase in terms of type frequency among the Polish students. Moreover, on both sides there are developments in language usage that seem to be connected with an increase in academic expertise.

The Impact of Social Networks on Language Learning: A Comprehensive Analysis

The ever-increasing pervasiveness of social networks has radically changed how language learning is conceptualized and practically experienced. This paper explores the role that popular social networking platforms such as Facebook and Instagram, and some language-specific applications such as HelloTalk and Tandem, play in language acquisition. A comprehensive analysis has been done of the existing literature and is supplemented with empirical data gathered through surveys and interviews conducted with language learners themselves. Thus, the investigation aims at pointing out the opportunities created by social networks in respect of vocabulary and grammar acquisition and of intercultural understanding, as well as the critical challenges that come along with the observation of non-standard language forms and the tendency toward digital distractions. Conclusions are drawn that even though social networks offer deeply authentic input and social interaction contributing to the development of linguistic and cultural competence, they need to be carefully embedded within a structured language education in order to optimize the learning effect. Furthermore, the paper discusses implications for educators and recommendations for good practice in using social networks as supplementary language learning tools.

Analysis of the Use of Various Languages in Msme Digital Marketing on Instagram: Case Study of Pukis Kota Baru

The rapid development of technology requires MSME Entrepreneurs to be more creative and innovative. Instagram is one of the Social Media that is widely used in promoting their products today. Like the @pukiskotabaru account which uses Instagram as a digital marketing tool. The purpose of this study is to determine the type of use of language varieties in video content on the @pukiskotabaru Instagram account and assess the effectiveness of the use of language varieties by the @pukiskotabaru Instagram account in attracting attention and influencing consumers. In this study, researchers used qualitative methods with data collection techniques then used content analysis techniques, where researchers collected several video content to find several interesting posts or videos in the process of digital marketing of their products. The results of this study indicate that the use of language varieties in the video content of the @pukiskotabaru Instagram account consists of spoken language varieties, written language varieties, and nonstandard language varieties, the use of persuasive written language varieties and strong visuals to attract consumer interest and the use of these language varieties has proven to be quite effective in attracting attention and influencing consumers.

Sequence-to-Sequence Models and Their Evaluation for Spoken Language Normalization of Slovenian

Sequence-to-sequence models have been applied to many challenging problems, including those in text and speech technologies. Normalization is one of them. It refers to transforming non-standard language forms into their standard counterparts. Non-standard language forms come from different written and spoken sources. This paper deals with one such source, namely speech from the less-resourced highly inflected Slovenian language. The paper explores speech corpora recently collected in public and private environments. We analyze the efficiencies of three sequence-to-sequence models for automatic normalization from literal transcriptions to standard forms. Experiments were performed using words, subwords, and characters as basic units for normalization. In the article, we demonstrate that the superiority of the approach is linked to the choice of the basic modeling unit. Statistical models prefer words, while neural network-based models prefer characters. The experimental results show that the best results are obtained with neural architectures based on characters. Long short-term memory and transformer architectures gave comparable results. We also present a novel analysis tool, which we use for in-depth error analysis of results obtained by character-based models. This analysis showed that systems with similar overall results can differ in the performance for different types of errors. Errors obtained with the transformer architecture are easier to correct in the post-editing process. This is an important insight, as creating speech corpora is a time-consuming and costly process. The analysis tool also incorporates two statistical significance tests: approximate randomization and bootstrap resampling. Both statistical tests confirm the improved results of neural network-based models compared to statistical ones.

Impact of articles written in non-alphabet languages.

Nowadays, English is the lingua franca of science, and the reference lists in most English articles are dominated by other English articles. Publications in languages other than English are most often in French, Italian, Spanish, or German. The minority written languages, that is, non-alphabet languages, have often not been included in reference lists in the scientific literature. However, to accord with the "diversity, equity, and inclusion" concept, non-alphabet languages should be included and discussed. Failure to cite articles in non-alphabet or non-standard languages ignores knowledge that could be useful to both the author and the reader. We hope the present article will promote more discussion of this often-overlooked topic.

Students’ attitudes towards an instructor’s foreign accent and non-standard language variety

AbstractThis study reports the outcomes of a speaker evaluation experiment conducted in a higher educational context in Flanders, in which we investigated the influence of language variety (Standard vs. Colloquial Dutch), accent (Flemish vs. Eastern European) and name (Flemish vs. Eastern European) on students’ perceptions of a female university instructor. The results suggest that participants exhibited a relatively high level of tolerance toward both non-conforming speech and non-conforming speakers. Whereas Colloquial Dutch scored lower than Standard Dutch on standardness, we observed no negative effects of Colloquial Dutch on the teacher’s didactic competence, status, or social attractiveness. We did not find any evidence of a negative bias triggered by an Eastern European name. Whereas the Eastern European accent did have a negative impact on the teacher’s social attractiveness, we did not find any evidence of an accent bias affecting judgements of the teacher’s didactic competence and status.

GRNet: a graph reasoning network for enhanced multi-modal learning in scene text recognition

Abstract Recent advancements in scene text recognition have predominantly focused on leveraging textual semantics. However, an over-reliance on linguistic priors can impede a model’s ability to handle irregular text scenes, including non-standard word usage, occlusions, severe distortions, or stretching. The key challenges lie in effectively localizing occlusions, perceiving multi-scale text, and inferring text based on scene context. To address these challenges and enhance visual capabilities, we introduce the Graph Reasoning Model (GRM). The GRM employs a novel feature fusion method to align spatial context information across different scales, beginning with a feature aggregation stage that extracts rich spatial contextual information from various feature maps. Visual reasoning representations are then obtained through graph convolution. We integrate the GRM module with a language model to form a two-stream architecture called GRNet. This architecture combines pure visual predictions with joint visual-linguistic predictions to produce the final recognition results. Additionally, we propose a dynamic iteration refinement for the language model to prevent over-correction of prediction results, ensuring a balanced contribution from both visual and linguistic cues. Extensive experiments demonstrate that GRNet achieves state-of-the-art average recognition accuracy across six mainstream benchmarks. These results highlight the efficacy of our multi-modal approach in scene text recognition, particularly in challenging scenarios where visual reasoning plays a crucial role.

Request for confirmation sequences in Low German

Abstract This article examines request for confirmation (RfC) sequences in Low German (LoG) conversation, a dialect variety of German. The study is based on both a quantitative analysis of 200 RfC instances and a qualitative analysis of selected excerpts in the framework of conversation analysis (CA). As for the question design of RfCs, declarative and phrasal formats, as well as modulations and tags prevail in the LoG data. Concerning the response design, LoG is characterized as a polarity system in which language contact with the high variety plays a decisive role in the answer possibility space. In particular, High German response tokens are predominantly used as unmarked response types, while LoG response tokens are deployed as marked types. Moreover, LoG seems to be a language between the poles of token- and repeat-type languages. Full repeats index different degrees of ‘markedness’ in LoG interaction. Contrary to previous studies on polar answers, repeats in LoG are frequently deployed as unmarked responses in subordinate lines of actions. Repeats are also used as more marked answers after understanding displays. This article attempts to stress the importance of investigating non-standard languages and variety contact in CA, thereby addressing the monolingual bias in research on polar questions.

Indonesian Slang Word Formation Processes in TikTok

Language changes over time due to social and cultural factors. These changes are evident through language varieties such as standard and non-standard languages, dialects, accents, and registers. This research focuses on one type of language variation, namely slang. Slang words show that language is constantly changing. For example, there are many new slang words that emerge and old ones that are no longer used or replaced. Slang also reflects people’s creativity because through slang we can see how someone can be very creative in making new words or modifying existing words. This research aims to identify the slang words that appear in the comments section of the TikTok during June to December 2022 and analyze the word formation process of each slang found. The authors used the qualitative descriptive method in order to present the data thoroughly. This study found that there were 39 slang words that appeared repeatedly and there were six most common word formation processes found in TikTok comments, namely blending, clipping, borrowing, acronym, affixation, and multiple processes. The most frequent processes are blending and clipping. The least frequent word formation processes are affixation and borrowing.

Analisis Karakter Bahasa Alay Kaum Remaja Di Kota Makassar

In daily life, human being can never escape from language. There are two types of languages; the standard language and the non-standard languages. In Indonesia, the standard language is Bahasa Indonesia, while the non-standard languages are the languages of vernacular (local languages) and sub-cultural languages (slang, jargon, etc). Nowadays, most of teenagers use the nonstandard language to communicate among their friends, which is called slang. There is a newslang in Indonesia which is called Alay language. The Alay language is popular among teenagers since 2008 until now. The purpose of this study were (1) to know the patterns used to modify Alay Language, (2) to know the effect of using Alay language on the standard form of Indonesian language, and (3) to find out the purpose of Alay Language used by teenagers in Makassar. This research uses descriptive analysis method. The research data were taken from the conversations that contained of Alay's words, which were previously made on the internet by Facebook social network users. Other supporting data were the questionnaires. The results of this study indicated that (1) There were no standard rules in modifying Alay Language, but the most common process was Substitution Process with a frequency of 38%. (2) The use of Alay Language had both the positive and negative effects on the existence of standard language, Indonesian language. (3) One of the reasons of using the Alay language was to be called “cool”.

Penggunaan Kata Tidak Baku dalam Penyampaian Konsep Geografi di Media Sosial

The use of social media has become an important part of our lives, including in the development of geographic science. However, we often see that there are many uses of non-standard words in conveying geographic concepts on social media which can interfere with the effectiveness of conveying information and understanding geographic concepts. The aim of this research is to increase students' understanding of the importance of learning and understanding non-standard language terms in social media. This research uses quantitative research methods by distributing questionnaires to geography education students at Medan State University. The results of the research conducted show that geography education students have a positive view of the use of non-standard words on social media because they can increase students' understanding and interest in learning about geographic concepts.

Online anti-immigrant discourse in Germany: ethnographically backed analysis of user comments

This article investigates discourse- and language-specific features of online anti-immigrant extreme speech in Germany. We analyze a context rich dataset collected and annotated through a collaborative effort involving fact-checkers, ethnographers and natural language processing (NLP) researchers. Using a bottom-up annotation scheme, we capture the nuances of the discourse and develop a typology of lexical innovations. The analysis combines thematic and critical discourse analysis with a linguistic perspective, revealing that direct forms of racism intertwine with argumentative forms of antagonism and playful word games within anti-immigrant discourses, in ways that center around narratives of victimhood and perceived threats from migrants. We further show how the specific conditions in Germany, including strict legal regulations of speech, have shaped the emergence of a non-standard language variety in and through anti-immigrant discourse, which helps the discourse community maintain group identity. The ethnographically backed analysis provides a granular understanding of the phenomenon of online extreme speech in the German context, contributing to the broader field of discourse studies and offering insights into the varieties within anti-immigrant discourse.

Puerto Rican welfare queens and the semiotics of respectability: The language of race, class, and gender

AbstractIn this article, we explore how raciolinguistic parody functions in a society that hegemonically denies racial divisions. Through an analysis of Puerto Rican comedian Natalia Lugo's YouTube portrayals of her character, Francheska the Yal ‘welfare queen,’ we argue that covert racialization operates through a semiotics of respectability, whereby disreputable forms of femininity, class expression, and nonstandard language are co‐indexical with the yal’s failure to normatively “whiten” herself. We contend that US colonial narratives that scapegoat poor women of color for the island's poverty are reconstructed in Lugo's parodies by depicting the yal as provincial and excessive. Lugo's performative choices underscore the interplay of linguistic, material, and discursive elements that marginalize the yal, enabling parody without challenging structural inequalities. Our analysis sheds light on the ways in which semiotic practices reify such social hierarchies where they are systemically denied.

Enhancing Durrotalk Chatbot Accuracy Utilizing a Hybrid Model Based on Recurrent Neural Network (RNN) Algorithm and Decision Tree

DurroTalk, a chatbot for new student admissions at Pondok Pesantren Durrotu Ahlissunnah Waljamaah, Semarang, integrates a hybrid model with Recurrent Neural Network (RNN) and Decision Tree. RNN, the base model, employs Natural Language Processing (NLP) to understand sentence structure and context, overcoming vanishing gradient through LSTM layers. The Decision Tree normalizes words, addressing slang and synonyms. The hybrid model boosts chatbot accuracy by 9%, reaching 77% from the initial 68%. This research signifies progress in integrating artificial intelligence into traditional education, showcasing a chatbot adept at handling non-standard language. Decision Tree integration enhances overall performance, making the chatbot proficient in understanding user inputs and generating contextually relevant responses. This study exemplifies the potential of AI, particularly chatbot technology, in modernizing educational processes at traditional institutions.