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Culture is considered a critical aspect of social media usage. The purpose of this paper is to explore how cultures and languages influence multilingual users' cross-cultural information sharing patterns.

This study used a crowdsourcing survey with Amazon Mechanical Turk to collect qualitative and quantitative data from 355 multilingual users who utilize two or more languages daily. A mixed-method approach combined statistical, and cluster analysis with thematic analysis was employed to analyze information sharing patterns among multilingual users in the Chinese cultural context.

It was found that most multilingual users surveyed preferred to share in their first and second language mainly because that is what others around them speak or use. Multilingual users have more diverse sharing characteristics and are more actively engaged in social media. The results also provide insights into what incentives make multilingual users engage in social media to share information related to Chinese culture with the MOA model. Finally, the ten motivation factors include learning, entertainment, empathy, personal gain, social engagement, altruism, self-expression, information, trust and sharing culture. One opportunity factor is identified, which is convenience. Three ability factors are recognized consist of self-efficacy, habit and personality.

The findings are conducive to promoting the active participation of multilingual users in online communities, increasing global resource sharing and information flow and promoting the consumption of digital cultural content.

This study aims to analyze translanguaging practices and beliefs of Iranian English for General Purposes (EGP) teachers and find discrepancies between the practice and perception of educators in bi/multilingual species in Iranian educational settings.

The study involved interviewing ten teachers and observing six of their sessions, which yielded qualitative data.

The results showed that the participating teachers produced recurring themes such as the significance and limitations of translanguaging, techniques for training multilingual learners and the restrictions imposed by policies that discourage the use of L1 in language institutes in Iran. A noteworthy observation made in this investigation was that educators who possessed competency in three or more languages exhibited greater endorsement of translanguaging in both their perceptions and practices.

This study has significant implications for instructors, teacher trainers and policymakers operating within multilingual environments. It serves as a pioneering study that invites a productive synergy between Western and Asian researchers in exploring bi/multilingual spaces within Asian educational contexts.

This study brings a fresh perspective to the current body of research on teacher agency in bi/multilingual educational settings. By utilizing qualitative methods, it offers unique and original insights. Particularly noteworthy is the discovery that educators who are proficient in three or more languages are more inclined to support translanguaging. This observation adds a distinctive understanding of translanguaging in language education. It opens up new possibilities for exploring the application and efficacy of the translanguaging approach in Asian bi/multilingual spaces in education.

The purpose of this paper is to explore issues pertaining to monolingual ideology in the United States and the challenges in terms of career identity and development for multilingual individuals.

This conceptual paper provides a discussion of the relevant literature pertaining to linguistic diversity, language ideologies, career identity and career development, and offers a critical conceptual framework for understanding career development in linguistically diverse, multilingual contexts.

Based on a critical review of literature, this paper proposes a conceptual framework which can be used to address linguistic issues that may otherwise encourage discrimination and inequity in the workplace.

This paper addresses the gap in career development literature by proposing a critical conceptual framework that integrates language as an important element of one’s career identity.

The purpose of this study is to examine Indian language journals published in Arts, Humanities and Social Sciences (AHSS) included in the UGC-CARE list, which is an initiative of the University Grants Commission (UGC) of India. This study argues that although these journals do not appear in international databases, they are valuable because they frequently publish and have published for years, opinions, memoirs and critical review articles, especially the local culture.

This study examines 298 journals categorised into two groups: monolingual (189) and multilingual (109). The first group included 189 journals published in 15 Indian languages. Monolingual journals were examined using five criteria: year of publication, subject area, frequency, language and geographical zone of the publisher. Multilingual journals analysed as per languages covered.

The analysis reveals that the UGC-CARE List includes journals published between 1899 and 2019. The most common languages are Hindi (67), Urdu (31), Sanskrit (9) and Marathi (26). The frequency of majority (114) of journals is quarterly. Associations, universities, individual publishers and learned societies as publishers are dominant. Analysis of multilingual journals indicated that the highest number of journals (34) are published in English and Hindi.

Journals that fulfil the stringer criteria of three UGC-CARE journal analysis protocols find a place in the CARE List. The list is dynamic and is updated quarterly to maintain its currency and therefore its credibility. The list is available at http://ugccare.unipune.ac.in and is the list preferred by Indian Higher Education Institutes.

UGC-CARE List includes journals published by Indian publishers especially in the fields of Arts, Humanities and Social Sciences. It is the first initiative to battle against the predatory journals and effort to bring the Indian legacy of journals on the world map of journals and periodicals.

Genre classification of songs based on lyrics is a challenging task even for humans, however, state-of-the-art natural language processing has recently offered advanced solutions to this task. The purpose of this study is to advance the understanding and application of natural language processing and deep learning in the domain of music genre classification, while also contributing to the broader themes of global knowledge and communication, and sustainable preservation of cultural heritage.

The main contribution of this study is the development and evaluation of various machine and deep learning models for song genre classification. Additionally, we investigated the effect of different word embeddings, including Global Vectors for Word Representation (GloVe) and Word2Vec, on the classification performance. The tested models range from benchmarks such as logistic regression, support vector machine and random forest, to more complex neural network architectures and transformer-based models, such as recurrent neural network, long short-term memory, bidirectional long short-term memory and bidirectional encoder representations from transformers (BERT).

The authors conducted experiments on both English and multilingual data sets for genre classification. The results show that the BERT model achieved the best accuracy on the English data set, whereas cross-lingual language model pretraining based on RoBERTa (XLM-RoBERTa) performed the best on the multilingual data set. This study found that songs in the metal genre were the most accurately labeled, as their text style and topics were the most distinct from other genres. On the contrary, songs from the pop and rock genres were more challenging to differentiate. This study also compared the impact of different word embeddings on the classification task and found that models with GloVe word embeddings outperformed Word2Vec and the learning embedding layer.

This study presents the implementation, testing and comparison of various machine and deep learning models for genre classification. The results demonstrate that transformer models, including BERT, robustly optimized BERT pretraining approach, distilled bidirectional encoder representations from transformers, bidirectional and auto-regressive transformers and XLM-RoBERTa, outperformed other models.

This study aims to explore motives behind teachers' and students' use of translanguaging and how they use it in Tanzanian public secondary school classrooms.

Data were collected using interviews and non-participant observations.

The findings indicate that translanguaging was used to facilitate content comprehension, promote classroom interaction and increase students' motivation to learn. Translanguaging was implemented using three strategies: paraphrasing an English text into Kiswahili, translating an English text into its Kiswahili equivalent and word-level translanguaging.

By highlighting the motivations for translanguaging and corresponding strategies associated with translanguaging pedagogy in the Tanzanian context, this study has significant practical implications for teachers and students to showcase their linguistic and multimodal knowledge, while fostering a safe learning space that relates to students' daily experiences.

The study offers new insights into previous research on the role of language-supportive pedagogy appropriate for teachers and students working within bi-/multilingual education settings.

This article, written by a multilingual learner program (MLP) specialist, provides a first-hand account of how a professional development school (PDS) (school–university partnership school) promotes teacher advocacy.

Due to the subject of the piece, no research methods were necessary.

Due to the subject of the piece, there are no findings.

The teacher details the teacher's educational journey from intern to doctoral candidate.

It has come to the attention of the publisher that the article Zeroual, I. and Lakhouana, A. (2020), “MulTed: a multilingual aligned and tagged parallel corpus”, published in Applied Computing and Informatics, https://doi.org/10.1016/ACI-j.aci.2018.12.003 was published twice due to a production error while onboarding the journal. The original article can be seen here: https://doi.org/10.1016/j.aci.2018.12.003

Understanding linguistic profiling and its substantial consequences on employee career development is essential in diverse workplaces. This study utilizes Levinson’s eras and career development theories to analyze the complicated relationship between linguistic profiling and biases, which hamper employee career development.

This study used an interpretive methodology and conducted thematic data analysis. It documented lessons learned from diverse viewpoints through semi-structured interviews with 19 participants conducted in November and December 2022.

The study demonstrates that linguistic discrimination occurs in diverse workplaces. After data exploration, four intriguing themes appeared. The first theme was related to employees who were discriminated against because of various languages. This shows how often language choice affects employees. The second theme examined how linguistic profiling intersected with marginalized groups, increasing discrimination. The third theme, linguistic profiling and career development showed that bias had a huge influence on career progression. The fourth theme emphasizes organizational policies for preventing language discrimination, promoting career growth and inclusive organizations.

This study advances the understanding of linguistic profiling and career development in a multilingual society. In addition, it furthers discourse and provides ways to minimize biases, creating a more inclusive workplace environment.

The primary objective was to develop a user-centered mobile health application (app) tailored to the specific health information needs of among immigrant women from diverse backgrounds in Korea.

In-depth interviews were conducted with 24 immigrant women to gain insights into their health information-seeking behavior. Based on the findings, a mobile app was designed and developed. A beta version of the app underwent validation by an MD and seven expert reviewers who assessed the app for content accuracy and conformance to mobile heuristics. Last, immigrant women (n = 12) evaluated the usability of the app.

The study revealed that the interviewed immigrant women had strong health information needs related to pregnancy and parenting. Most of them used multiple sources to find and verify health information. Language barriers were identified as a major obstacle to accessing and evaluating health information. The results of the user test indicated that the app effectively facilitated study participants' search for reliable health information, meeting their specific needs.

This research extended the literature by addressing the limited availability of mobile apps tailored to the health information needs of immigrant women in Korea.

By incorporating multilingual support and focusing on pregnancy and parenting information, the health app serves as a valuable tool to bridge the gap in health information access and to facilitate the well-being of immigrant women in the country.