Hasil untuk "Chinese language and literature"

H. Crompton, D. Burke

This systematic review provides unique findings with an up-to-date examination of artificial intelligence (AI) in higher education (HE) from 2016 to 2022. Using PRISMA principles and protocol, 138 articles were identified for a full examination. Using a priori, and grounded coding, the data from the 138 articles were extracted, analyzed, and coded. The findings of this study show that in 2021 and 2022, publications rose nearly two to three times the number of previous years. With this rapid rise in the number of AIEd HE publications, new trends have emerged. The findings show that research was conducted in six of the seven continents of the world. The trend has shifted from the US to China leading in the number of publications. Another new trend is in the researcher affiliation as prior studies showed a lack of researchers from departments of education. This has now changed to be the most dominant department. Undergraduate students were the most studied students at 72%. Similar to the findings of other studies, language learning was the most common subject domain. This included writing, reading, and vocabulary acquisition. In examination of who the AIEd was intended for 72% of the studies focused on students, 17% instructors, and 11% managers. In answering the overarching question of how AIEd was used in HE, grounded coding was used. Five usage codes emerged from the data: (1) Assessment/Evaluation, (2) Predicting, (3) AI Assistant, (4) Intelligent Tutoring System (ITS), and (5) Managing Student Learning. This systematic review revealed gaps in the literature to be used as a springboard for future researchers, including new tools, such as Chat GPT. A systematic review examining AIEd in higher education (HE) up to the end of 2022. Unique findings in the switch from US to China in the most studies published. A two to threefold increase in studies published in 2021 and 2022 to prior years. AIEd was used for: Assessment/Evaluation, Predicting, AI Assistant, Intelligent Tutoring System, and Managing Student Learning.

F. Escobedo, Vincenzo Giannico, C.Y. Jim et al.

Abstract Approaches and concepts nurturing interdisciplinary knowledge on urban ecosystems have evolved over recent decades and adopted a series of metaphors, including Ecosystem services (ES), Green infrastructure (GI), and Nature-based solutions (NBS). Similarly, research and promotion of urban forests (UF) and their multiple functions have recently grown as a means to address issues affecting urban areas throughout the world. Regardless of the metaphor used, urban forestry has historically provided a common language, science-based practices, and experiences for planning and managing trees and green spaces in cities to provide such benefits. Therefore, we conducted a review of the literature to better understand the origin, trends, and evolution of these metaphors and their institutional and contextual interpretations. Relationships among terms, publication trends and the studies’ countries of origin were then used to identify the nexus between urban forestry and these metaphors. We found that ES appears in 2006, GI in 2007 and NBS in 2015. Definitions based on seminal academic publications are now included in national-level policy instruments in several countries and regions. However, in terms of English language publications, the United States leads by a notable margin followed by China, larger European Union countries, Brazil, Australia, and Canada. Similarly, the North-South divide is evident in terms of scientific publication productivity and funding for this type of research. Science and evidence-based guidelines and solutions for integrating and implementing urban forestry practices and experiences are found in several international publications. We suggest that such metaphors, and their socio-political implications, are not as important as the inherent messages. Indeed, changes in both discipline and language are key for communicating the documented importance of urban forestry for enhancing human well-being. A set of criteria that could be adopted to guide the use of these and future metaphors is also presented.

Lin Luan, Jong-Chao Hong, M. Cao et al.

ABSTRACT During the COVID-19 pandemic period, a growing number of learning activities are taking place in online contexts. Along with the adversity in the online course of target language learning, student engagement has been considered important to improve learners’ academic achievements of the target language. Although there has been a growing interest in the relationship between students’ perceived social support and their online learning engagement, the literature lacks an in-depth investigation of the intricate relations between these two constructs in an online English as a foreign language (EFL) learning setting during the pandemic. To address this gap, this study attempts to develop a model which depicts the relationships between students’ perceived social support and their online English learning engagement. A total of 615 university students in China were invited to take part in the study. By conducting structural equation modeling, the results confirmed the mediational model in which behavioral engagement completely mediated the relationships between social support (teacher support and peer support) and three other types of student engagement (cognitive, emotional and social engagement). These findings suggest designing effective instruction and developing support strategies in online teaching to enhance EFL learners’ engagement during the COVID-19 lockdown.

L. Berrang‐Ford, Anne J. Sietsma, M. Callaghan et al.

Summary Background The global literature on the links between climate change and human health is large, increasing exponentially, and it is no longer feasible to collate and synthesise using traditional systematic evidence mapping approaches. We aimed to use machine learning methods to systematically synthesise an evidence base on climate change and human health. Methods We used supervised machine learning and other natural language processing methods (topic modelling and geoparsing) to systematically identify and map the scientific literature on climate change and health published between Jan 1, 2013, and April 9, 2020. Only literature indexed in English were included. We searched Web of Science Core Collection, Scopus, and PubMed using title, abstract, and keywords only. We searched for papers including both a health component and an explicit mention of either climate change, climate variability, or climate change-relevant weather phenomena. We classified relevant publications according to the fields of climate research, climate drivers, health impact, date, and geography. We used supervised and unsupervised machine learning to identify and classify relevant articles in the field of climate and health, with outputs including evidence heat maps, geographical maps, and narrative synthesis of trends in climate health-related publications. We included empirical literature of any study design that reported on health pathways associated with climate impacts, mitigation, or adaptation. Findings We predict that there are 15 963 studies in the field of climate and health published between 2013 and 2019. Climate health literature is dominated by impact studies, with mitigation and adaptation responses and their co-benefits and co-risks remaining niche topics. Air quality and heat stress are the most frequently studied exposures, with all-cause mortality and infectious disease incidence being the most frequently studied health outcomes. Seasonality, extreme weather events, heat, and weather variability are the most frequently studied climate-related hazards. We found major gaps in evidence on climate health research for mental health, undernutrition, and maternal and child health. Geographically, the evidence base is dominated by studies from high-income countries and China, with scant evidence from low-income counties, which often suffer most from the health consequences of climate change. Interpretation Our findings show the importance and feasibility of using automated machine learning to comprehensively map the science on climate change and human health in the age of big literature. These can provide key inputs into global climate and health assessments. The scant evidence on climate change response options is concerning and could significantly hamper the design of evidence-based pathways to reduce the effects on health of climate change. In the post-2015 Paris Agreement era of climate solutions, we believe much more attention should be given to climate adaptation and mitigation options and their effects on human health. Funding Foreign, Commonwealth & Development Office.

Lu LU, Juanyu WU, Seping DAI et al.

ObjectiveCultural ecosystem service (CES) refer to the intangible benefits that humans obtain from ecosystems, such as spiritual satisfaction, cognitive development, and aesthetic experiences. The assessment of their value is of great significance for revealing the mechanisms of ecosystem benefits and enhancing human well-being. This research aims to systematically analyze the progress of CES assessment driven by multi-source big data, explore cutting-edge trends, and identify future directions.MethodsThe search query for the Web of Science core database was TS = (“ecosystem*” AND “cultural service*”) AND (TS = valuation OR TS = evaluate OR TS = evaluation OR TS = assessment OR TS = quantification). The search query for the China National Knowledge Infrastructure (CNKI) database was SU%= “value assessment” and SU%= “evaluation” and SU% = “quantitative research” and SU% = “ecosystem cultural services”. We conducted separate searches for foreign-language and Chinese-language literature, manually screened the literature that applied multi-source big data for CES assessment, and ultimately obtained 273 foreign-language articles and 246 Chinese-language articles from 2000 to 2024. The study organized research findings across four dimensions: big data types, CES value types, assessment objects, and assessment methods. It also discussed current research opportunities, challenges, and future trends. Based on the literature review results, this study systematically constructed a CES assessment framework based on multi-source big data, with a core workflow comprising “assessment object−CES value type−big data type−assessment method” and four core modules.Results1) The CES assessment paradigm is shifting from traditional economic accounting to intelligent assessment. Statistics show that approximately 70% of CES assessment studies have achieved paradigm innovations through the application of multi-source big data, primarily manifested in four aspects: expansion of CES value types, refinement of assessment objects, and innovation in assessment methods. 2) With the widespread application of big data, the data foundation for CES assessment has broken through traditional limitations, forming a diversified landscape combining government-published data (such as ecological environment data, population and economic data, etc.) with user-generated data (such as social media data, point of interest (POI) data, location-based communication data, etc.). Research progress in CES assessment system has shown a progressive trend: from early reliance on government-disclosed data, to the expansion of user-generated data, and then to multi-modal data. This trend has significantly improved the accuracy, spatio-temporal coverage, and scenario applicability of assessment research. A deeper change lies in the fact that the diversification of data sources is driving a shift in the CES assessment paradigm from “supply-driven” to “supply-demand coordination”. 3) As the application and adaptability of multi-source big data have improved, the development of assessment objects has shown a trend toward focusing and refining the scope of research, shifting from early regional-scale natural ecosystems (farmland, forests, marine ecosystems) to urban built environments, with a focus on densely populated urban ecosystems (urban green spaces, urban parks, green infrastructure). From 2020 to 2024, urban environments closely related to daily life, such as urban communities, streets, and rooftop gardens, have become hotspots in CES research. 4) In the early stages of research, CES assessment primarily relied on monetary economic methods and manual evaluation methods. With the growing demand for big data analysis, ecological analysis models have been widely applied, and artificial intelligence technologies such as machine learning and deep learning have emerged as the latest assessment methods. When addressing the massive demand for data analysis, emerging machine learning and deep learning models facilitate the processing of large datasets and the extraction of in-depth information, significantly enhancing the efficiency and accuracy of CES assessment research. Among these, CES assessment methods based on natural language processing (NLP) and computer vision (CV) recognition technologies are particularly representative and have become a hot research focus both domestically and internationally in recent years. Specifically, classic deep learning models such as ResNet, EfficientNet, YOLO, and BERT, as well as emerging large language models like GPT and Gemini, are among the most frequently used assessment tools. 5) This study established a CES assessment framework based on big data, forming an expandable and transferable standardized assessment workflow through a cascading mechanism of “assessment object−CES value type−big data type−assessment method”, providing an innovative paradigm for ecosystem service research of different scales, scopes, and types.ConclusionIn summary, early CES research focused on economic value calculation and environmental quality assessment. With the increasing demand for high-quality human settlements, the research focus has gradually shifted to the socio-cultural dimension, emphasizing cultural benefits such as health benefits, identity recognition, and spiritual value, driving CES research into a new phase of human well-being and perception assessment. Future research should strengthen the application of multi-source big data integration and interdisciplinary methods, with a focus on constructing standardized CES assessment frameworks to enhance their theoretical explanatory power.

Rosario Catelli, Serena Pelosi, Massimo Esposito

Recent evolutions in the e-commerce market have led to an increasing importance attributed by consumers to product reviews made by third parties before proceeding to purchase. The industry, in order to improve the offer intercepting the discontent of consumers, has placed increasing attention towards systems able to identify the sentiment expressed by buyers, whether positive or negative. From a technological point of view, the literature in recent years has seen the development of two types of methodologies: those based on lexicons and those based on machine and deep learning techniques. This study proposes a comparison between these technologies in the Italian market, one of the largest in the world, exploiting an ad hoc dataset: scientific evidence generally shows the superiority of language models such as BERT built on deep neural networks, but it opens several considerations on the effectiveness and improvement of these solutions when compared to those based on lexicons in the presence of datasets of reduced size such as the one under study, a common condition for languages other than English or Chinese.

Seokmin Yoon, Youngjin Kim, Yi Yang

In the late Joseon dynasty, many Koreans crossed the border between Joseon and Qing for survival. They then migrated to Manchuria, in the Qing territory, around Mt. Baekdu. In the late 1900s, Japan seized diplomatic and military control of Korea, and in 1910, Korea was annexed by Japan. Many Koreans then moved to the Manchurian region of China. Religion played an important role in the large Korean community formed in Manchuria after the 1910s. During this period, Korean immigrant communities that were centered on religion were established in Manchuria. Among the many religions, Daejonggyo (大倧敎) places great emphasis on national consciousness, and it was an active component of the anti-Japanese armed independence movement to restore national sovereignty. In particular, Daejonggyo claimed that Dangun (檀君), the founder of the Korean people, came down from heaven, established the first nation of the Korean people on Mt. Baekdu, and governed the surrounding area. Accordingly, Daejonggyo considered the Manchurian region to be the ancient territory of the Korean people. In addition, Daejonggyo presented the concept of the Baedal nation as a Dangun lineage and included not only the Korean people but also various northern ethnic groups, such as the Manchurian people. By doing so, Daejonggyo converged not only the Korean Peninsula and the Joseon nation (minjok, 民族) but also the Manchurian region and various ethnic groups in Manchuria into its own territory and people. Through this, Daejonggyo believers not only secured the legitimacy of residing in Manchuria but also gained the justification to drive out the Japanese and restore the Korean peninsular ancient territory.

Eyu E, Wending Liu, Yuanzhe Li

Abstract In English-medium postgraduate classrooms, particularly within MSc/MA TESOL programs in the UK, many Chinese students hesitate to pose questions despite possessing advanced English proficiency. This qualitative study aims to address three critical gaps in the literature: (1) the underexploration of postgraduate learners’ affective experiences in immersive English-speaking contexts, (2) the neglect of routine classroom interactions such as question-posing compared to formal speaking tasks, and (3) the limited understanding of how cultural and educational traditions shape anxiety in graduate-level TESOL programs. Drawing on semi-structured interviews with five Chinese postgraduates, the research investigates the psychological, cultural, and contextual dimensions of question-posing anxiety. Findings highlight key contributing factors—including linguistic insecurity, fear of negative evaluation, perceived inadequacy of questions, cross-cultural classroom norms, and the legacy of prior educational socialization—manifesting in both cognitive and physiological symptoms. Students also reported employing adaptive strategies such as self-talk, peer rehearsal, and deliberate body language to navigate these challenges.

Meng-jie Dong, B. Peng, Zhen-feng Liu et al.

BackgroundThe prevalence of HIV among men who have sex with men (MSM) has become a significant public health challenge. The aim was to comprehensively estimate the national prevalence of HIV among MSM and its time trends through a large-scale systematic analysis.MethodsSystematic search of Cochrane Library, PubMed, EMBASE, CNKI, VIP, and Wanfang Data databases without language restriction for studies on the prevalence of HIV among MSM published before Dec.31, 2018. Studies were eligible for inclusion if they were published in the peer-reviewed literature and used validated assessment methods to assess the prevalence of HIV among MSM. Estimates were pooled using random-effects analysis.ResultsData were extracted from 355 cross-sectional studies (571,328 individuals) covered 59 cities from 30 provinces and municipalities of China. The overall national prevalence of HIV among MSM from 2001 to 2018 was estimated to be 5.7% (95% CI: 5.4–6.1%), with high between-study heterogeneity (I2 = 98.0%, P <  0.001). Our study showed an increased tendency in the HIV prevalence as time progressed by meta-regression analysis (I2 = 95.9%, P <  0.0001). HIV prevalence was the highest in those aged 50 years and older with HIV prevalence of 19.3% (95%CI: 13.1-27.4%, N = 13). HIV was more prevalent in the illiterate population (16.8%), than in those who had received an education. Although the internet was a major venue for Chinese MSM seeking male sex partners (35.6, 95%CI: 32.3-39.9%, N = 101), seeking MSM in bathhouses/saunas had the highest associated prevalence of HIV (13.4, 95%CI: 10.3-17.1%, N = 22). The HIV prevalence among MSM varied by location: compared with other regions in China, HIV was highly prevalent among MSM in the southwest (10.7, 95%CI: 9.3-12.2%, N = 91). Compared to participants who sometimes or always used condoms, participants who had never used a condom in the past 6 months had a higher risk of HIV infection, with odds ratios of 0.1 (95%CI: 0.08-0.14).ConclusionsOur analysis provided reliable estimates of China’s HIV burden among MSM, which appears to present an increasing national public health challenge. Effective government responses are needed to address this challenge and include the implementation of HIV prevention.

Anders Søgaard

Most, if not all, philosophers agree that computers cannot learn what words refers to from raw text alone. While many attacked Searle’s Chinese Room thought experiment, no one seemed to question this most basic assumption. For how can computers learn something that is not in the data? Emily Bender and Alexander Koller ( 2020 ) recently presented a related thought experiment—the so-called Octopus thought experiment, which replaces the rule-based interlocutor of Searle’s thought experiment with a neural language model. The Octopus thought experiment was awarded a best paper prize and was widely debated in the AI community. Again, however, even its fiercest opponents accepted the premise that what a word refers to cannot be induced in the absence of direct supervision. I will argue that what a word refers to is  probably learnable from raw text alone. Here’s why: higher-order concept co-occurrence statistics are stable across languages and across modalities, because language use (universally) reflects the world we live in (which is relatively stable). Such statistics are sufficient to establish what words refer to. My conjecture is supported by a literature survey, a thought experiment, and an actual experiment.

Linheng Li, Can Wang, Jing Gan et al.

Abstract Emission data collection has always been a significant burden and challenge for Chinese counties to develop a CO2 emission inventory. This paper proposed a fuel consumption-based method to develop a local-specific CO2 emission rate database for Chinese counties using only open-source big data. Localized vehicle fuel consumption data is obtained through natural language processing (NLP) algorithm and large language model (LLM). The emission rates derived by our proposed method are consistent with field test results in literature. Besides, the CO2 emission estimation results using local-specific traffic activity data indicate that our method could effectively improve the accuracy of vehicle emission assessment. Compared with conventional method, the novel approach proposed in this paper can provide a pathway for convenient, universal, and cost-saving assessment for local scale CO2 emission rates. With this method, it is possible to formulate a local-specific CO2 emission database in various Chinese counties using only open-access big data.

Zhangwei Chen

Motivation and anxiety are two crucial factors influencing learning outcomes, yet limited empirical research on expectancy-value theory can be found within previous literature about Chinese undergraduate students studying English as a foreign language (EFL). Moreover, few studies have examined the interaction between motivation and skill-specific anxiety. Thus, the present study explored dimensions of task values of English learning, the relationship between expectancy, values and English language speaking anxiety (ELSA) among Chinese undergraduate EFL learners and their predictive power on spoken English proficiency. Two hundred twenty-three Chinese undergraduates completed a questionnaire about their spoken English proficiency, expectancy-value and ELSA items. The following results came to light: (1) task values in English learning had four facets; (2) different types of value were significantly positively correlated with each other, both expectancy and ELSA were significantly linked to cost value, and expectancy bore a significantly negative correlation with ELSA; (3) expectancy, ELSA and attainment and cost value separately predicted learning achievement, whereas only expectancy and value additively predicted learning achievement, where expectancy exerted a greater impact. These findings suggest that teachers should guide students to aim high and provide more opportunities for spoken English practice.

Samreen Kazi, S. Khoja, Ali Daud

Xiaoyang Li, Hao Feng, Hailong Yang et al.

Abstract This paper examines the potential of ChatGPT, a large language model, as a financial advisor for listed firm performance forecasts. We focus on the constituent stocks of the China Securities Index 300 and compare ChatGPT’s forecasts for major financial performance measures with human analysts’ forecasts and the realised values. Our findings suggest that ChatGPT can correct the optimistic biases of human analysts. This study contributes to the literature by exploring the potential of ChatGPT as a financial advisor and demonstrating its role in reducing human biases in financial decision-making.

Yuan Sang

In the field of foreign and second language (L2) teacher education, existing literature has emphasized the importance of examining language teacher identity in uncovering how L2 teachers grow professionally. However, there have been relatively few investigations into emerging pre-service L2 teachers’ language teacher identity at an early stage of professional development. Focusing on a group of pre-service teachers of English as a foreign language (EFL) in China who were in their first semester of study in English teacher education, the present research was set out to explore these emerging pre-service teachers’ beliefs and how their beliefs connected to teacher identities. Analyses of participants’ survey narratives showed that pre-service EFL teachers highlighted three significant aspects of their English language teacher identities, which were English teachers as ‘instructors’, as ‘individuals’, and as ‘English experts’. Results of three focal pre-service EFL teachers’ interviews provided further evidence to demonstrate how teachers’ beliefs linked to teacher identities. The significance of these findings and directions for future research were discussed. This study concluded with suggestions for supporting emerging pre-service L2 teachers’ professional growth in language teacher education.

Shin Yi Chew

In this first issue of Volume 33, we delve into the rich tapestry of linguistic diversity and academic discourse, showcasing a range of studies that shed light on various facets of language use, maintenance, and communication. The collection of articles in this issue offers valuable insights into the ever-evolving world of language. The first article in our lineup, Language Shift and Maintenance: A Case Study of the Telugu Community in Bagan Datoh, Perak (Malaysia), takes us to Bagan Datoh, Perak, where the Telugu language, despite being a minority language in Malaysia, continues to thrive in specific domains. This case study illuminates the dynamics of language choice among different generations and provides hope for the revitalization of Telugu among the younger generation. The second article, Metadiscourse Markers in Abstracts of Linguistics and Literature Research Articles from Scopus-Indexed Journals, shifts our focus to the world of academic writing, specifically the use of metadiscourse markers in abstracts. It highlights the crucial role these markers play in structuring and presenting research arguments. The comparative analysis between linguistics and literature abstracts provides valuable insights into disciplinary differences in the use of these markers. Our third article, An Exploratory Analysis of Linking Adverbials Used by Filipino, Pakistani, and Thai Writers of English, undertakes a contrastive interlanguage analysis, shedding light on how students from the Philippines, Pakistan, and Thailand use linking adverbials in their English academic writing. The importance of understanding the distinct production tendencies of various English varieties is emphasised in this article. Turning to a sensitive topic in the Malaysian context, the fourth article, Female Circumcision in Malaysia: Challenges and Lessons Learned in Using Focus Groups through an NGO-Academia Collaboration, explores female circumcision and the challenges faced in conducting research on this subject. It highlights the collaborative efforts between academia and a local NGO, offering valuable insights into data collection via focus group discussions. The fifth article, Prosodic Marking of New and Given Information in English and Mandarin by Chinese Speakers, ventures into the realm of prosody and its impact on language comprehension. Focusing on Chinese English as a Foreign Language learners, it investigates how Mandarin influences the prosodic marking of new and given information in English, shedding light on potential areas of misunderstanding. Our final article, Privacy Policy Pop-up: A Genre Analysis of Journal Websites’ HTTP Cookies, takes a dive into the world of online privacy and transparency. It analyses the communication of transparency through HTTP cookies on academic journal websites, uncovering the rhetorical strategies employed to inform users about data privacy. In this diverse collection of articles, we invite readers to explore the multifaceted world of language and academic discourse. Each study offers unique insights into the complexities of communication and the richness of linguistic diversity. We hope this issue serves as a valuable resource for scholars, researchers, and language enthusiasts alike, encouraging further exploration and understanding of these vital aspects of our academic and cultural landscape. Last but not least, I would like to express my heartfelt thanks to all the contributors, reviewers and readers of this Journal. My special thanks also go to all the  members of the Editorial Board and Advisory Board for their significant contributions. Editorial Board Prof. Dr. Stefanie Pillai  A.P. Dr. Paolo Coluzzi A.P.  Kim Keum Hyun Dr. Azlin Zaiti Zainal Dr. Charity Lee Chin Ai Dr. Ng Lee Luan Dr. Noor Aqsa Nabila binti Mat Isa Dr. Soh Siak Bie (journal manager) Dr. Thanalachime Perumal   International Advisory Board  Prof. Dr. Richard Fitzgerald (University of Macau, China) Prof. Dr. Stephen Hall (Sunway University, Malaysia) Prof. Dr. Jan Hardman (University of York, United Kingdom) Prof. Dr. Jason Miin-Hwa Lim (Universiti Malaysia Sabah, Malaysia) Prof. Dr. Dennis Tay (The Hong Kong Polytechnic University) Assoc. Prof. Dr. Shirley Dita (De La Salle University, Philippines) Assoc. Prof. Dr. Michelle M. Lazar (National University of Singapore, Singapore) Assoc. Prof. Dr. Jonathan Newton (Victoria University of Wellington, New Zealand) Dr. Mário Pinharanda-Nunes (University of Macau, China) The future issues of this Journal will be in the capable hands of Prof. Dr. Stefanie Pillai, whom I believe will be able to lead the Journal to greater heights. P.S.: An Appendix with a compilation of highlighted articles from the past five years is also included here for your reference.  

Wei Xiong

In the original publication (Xiong 2023), the funder is not directly related to the research in this paper [...]

Xiuyu Li, Evgeny S. Rybinok

This study is devoted to the analysis of lexico-semantic group of verbs, which express attitude to someone in Russian and the ways of their translation into Chinese. A group of emotional and evaluative verbs included in the lexico-semantic field of interpersonal relations is analyzed. The choice of the study material is determined by the fact that this group of verbs is one of the most frequent in the use and widely represented in the novel “Crime and punishment” by F.M. Dostoyevsky, occurring 561 times. The significance of this research lies in the absence of a special systematic study of this lexico-semantic group on the material of literature in Russian and Chinese languages, as well as in the need to develop a comprehensive research methodology, methods of comparative and contextual analyses. The study reveals the semantic features of verbs in the Russian and Chinese languages. It is established that the lexico-semantic group under study consists of verbs that are perceived as categorical-lexical semes “relation” and can have both positive and negative semantic meaning. The semes ‘positive attitude’, ‘love’, ‘faith’, ‘respect’, ‘compassion’, ‘pity’ and ‘negative attitude’, ‘suffering’, ‘doubt’, ‘fear’ are subjected to study. These features determine the structure of the group in question in the lexical and semantic system of the Russian and Chinese languages, are expanding the understanding of the content and structure of the group of verbs. The result of the study is that the analysis of interlingual gaps reveals the presence of incomplete lexical correspondence to a foreign language word. The analyzed linguistic material made it possible to identify similarities and differences in the semantics of verbs when translating the text of the novel into Chinese.

Chou Iris Yun-Chieh, Sang-Im Lee-Kim

This study presents empirical evidence from read versus interactive speech to shed light on the nature of the alveolar-retroflex sibilant merger by young speakers of Taiwan Mandarin (TM). TM speakers often merge the two sibilants through deretroflexion of the retroflex category. The results of the reading task showed that the variation is on a full continuum, from a complete merger to clear contrasts, and the merger is more prevalent among male speakers, demonstrating the impact of the social stigma associated with the merger. However, the results of the interactive task demonstrated that speakers who merged the contrast produced the retroflex sounds as distinct from their alveolar counterparts, revealing hidden structures in the mental lexicon. The mismatch between the abstract phonological knowledge and actual implementation in production suggests that the exposure to phonological systems of other speakers, especially those who make clear distinctions, has led to the incorporation of discrete categories into the phonological knowledge of the merged speakers. These findings suggest that large individual variation in the early stages of sound change may provide evidence for possible categories in a given language for language learners; however, their implementation may be further modulated by social as well as other phonetic factors.

Mac Aditiawarman Mac, Amelia Yuli Astuti Yuli

The language spoken by the masses of Indian descent in Padang is one of the social dialects that occurs in the city of Padang other than the Minangkabau dialect spoken by Chinese descendants, and the descendants of Nias. The ethnic customs of India in speaking and communicating have been accustomed to mixing their mother tongue with Minangkabau language, so that there has been a mixture of vocabulary that they say. Because the mixes are so swift, there has been mixed code-mixing in their language.               The approach in researching this problem is used in sociological approach to achieve the objectives of this research. The purpose of this study is to explain the language changes that occur among ethnic Indians in the city of Padang. The theory is implemented in researching the phenomenon of language changes that occur and studied by using linguistic theories. After obtaining the data, the authors make a formula of mixing code (code mixing) which is found in the speech of ethnic Indian in the city of Padang. This study uses field research methods to obtain significant data and literature study to obtain theories that will be used as the basic theory in this thesis. Techniques of collecting data, among others, by using qualitative methods, which in this case the authors obtain data through 7 people informants in accordance with the criteria NORM (Nonmobile Older Rural Males). From seven people as the informan, the writer can apply recording techniques  to obtain significant data.               The results of the research conducted, the writer finds language changes that are influenced by Minangkabau language, Chinese Padang language and Indonesian language. The changing that occur among others, change vowel /i/ become /e/ in the middle of the word, disappearance of consonant /h/ in the beginning, middle, and end of word. Consonant removal /r/ in the middle and end of word. The impingement  /to/  at the end of the word, vowel /u/ being /o/ in the middle and end of the word, consonant splitting /t/ to /k/, vowel /a/ being /o/ the consonant splitting /p/ into /?/, the /ŋ/ being /a/ at the end of the word, vowel /e/ being /a/ in the middle and beginning of the word. The disappearance of vowel /e/ in the middle of the word, the disappearance of consonant /d/ in the beginning and middle of the word, as well as the disappearance of consonant /p/ at the end of the word. The Indians ethnic code mixing can be formulated by using the theory of code mixing.