Common Words Research Articles

Application Of the National Corpus Of The Kazakh Language In Linguistic Research

National corpora are essential tools in modern linguistics, offering valuable data for analyzing language structures and their connection to the world.The primary goal of this study is to enhance the perception and analysis of the Kazakh language. It introduces a methodological approach that deepens the understanding of the structure and features of Kazakh.The research utilizes frequency analysis, syntactic parsing, and statistical methods to examine Kazakh language texts. The results demonstrate that the National Corpus provides extensive data for studying linguistic patterns. Frequency analysis identifies the most common words and phrases, while syntactic analysis uncovers patterns and connections between words. The study also highlights the variation in word usage and constructions, showing the language's adaptability to modern communication.The findings are applicable to lexicography, semantics, and syntax studies of the Kazakh language. Additionally, they offer practical benefits in language teaching, lexicographic resource creation, machine translation, and natural language processing.In conclusion, the research provides valuable tools for in-depth analysis of the Kazakh language, with broad applications across linguistic studies and practical fields.

Mothers with Breastfeeding Difficulty Report Increased Depressive Symptoms and Impaired Maternal-Infant Bonding on Social Media.

Background: Protection against postpartum depression is a commonly cited maternal benefit of breastfeeding. However, recent studies have found that negative breastfeeding experiences may actually increase the risk of depressive symptoms. Objective: To investigate women's self-reported associations between breastfeeding experiences and depressive symptoms on a social media platform. Study Design: An electronic search was conducted on Reddit of all original user posts using keywords "breastfeeding" and "depression" from February 2013 to July 2021. Relevant posts and corresponding comments were manually extracted, evaluated for inclusion and exclusion criteria, and analyzed for thematic content. Results: In total, 584 entries was analyzed. Mothers most frequently described difficulty breastfeeding as the cause of new onset mental health symptoms (53%); however, mothers breastfeeding without difficulty were also susceptible (20%). Mothers also reported exacerbated preexisting mental health symptoms-predominantly related to difficulty breastfeeding (17%), but again, others experienced no difficulty (6%). Common words included among all entries were "guilt" (17%), "fail" (14%), "pressure" (7%), "shame" (6%), and "alone" (6%). Among mothers mentioning bonding (n = 99), 58% reported that breastfeeding inhibited infant bonding, versus 1% enhanced bonding; furthermore, 63% reported increased bonding after switching to formula versus 8% unchanged and 6% decreased bonding. Nearly one-quarter (23%) of all posts described inadequate breastfeeding counseling. Finally, 9% of all posts reported a negative experience with health care providers versus 6% a positive experience. Conclusions: Mothers struggling to breastfeed may not experience the classically described benefits of breastfeeding, instead experiencing increased depressive and other mental health symptoms and impaired maternal-infant bonding. Furthermore, limited provider disclosure about potential breastfeeding challenges and alternatives to breastfeeding may exacerbate mental health symptoms associated with breastfeeding difficulties. Balanced information should be presented to mothers contemplating breastfeeding in order to minimize maternal perceptions of "failure."

Developing and Validating Monosyllabic Speech Materials with Psychometric Homogeneity for Young Adult Turkish-Azeri Speakers in Iran and Compiling the Equivalent Word Lists

Background and Aim: For the Word Recognition Score (WRS) test, homogenous lists of words with similar difficulty levels are needed. This study aimed to develop and validate Turkish-Azeri monosyllabic words with phonetic balance and psychometric homogeneity for the WRS test in young adult Turkish-Azeri speakers in Iran and to compile four 25-item word lists. Methods: In this cross-sectional/comparative study, four lists of 25 monosyllabic words with phonetic balance were created by extracting common words from Turkish-Azeri dialects and assessing them in terms of ease of use, familiarity, and relevance. Then, the lists were tested on 40 young adult Azari speakers aged 18–25 years to determine the validity and reliability. Results: All four lists showed adequate face and content validity. Cronbach’s alpha and split-half values for all four lists were above 0.9, indicating acceptable internal consistency and reliability. Construct validity was confirmed the factor analysis with one-dimensional variance of 77.9%, 80.0%, 79.9%, and 88% for the word lists 1 to 4, respectively, and reported the single-factor solution of the index in all four lists. Also, test-retest reliability with a two-week interval with Pearson correlation coefficients of the lists were 0.94, 0.97, 0.97, and 0.96, respectively. Conclusion: The four developed Turkish-Azeri word lists have phonetic balance and psychometric homogeneity with a high level of validity and reliability, which makes them suitable for evaluating the recognition of monosyllabic words by young adults in hearing centers of Azeri cities in Iran. Keywords: Speech audiometry; speech discrimination test; Azeri; monosyllabic; validity and reliability; psychometric function

Understanding perceptions of unfamiliar drinks using natural language in simulated drinking contexts

How do people make sense of new foods and beverages? Hop water is a recent example of a novel beverage category, advertised as either an alcohol-free, zero-calorie beer alternative or a more “natural” alternative to flavored seltzers. This study aimed to understand what individual or contextual factors may cause consumers to perceive hop water as more beer-like or more seltzer-like. Participants (43 regular seltzer-drinkers, 41 regular beer-drinkers, 45 people who regularly drink beer and seltzer, and 68 people who do not regularly drink either) tasted three commercially-available hop waters in one of three drinking contexts (apartment garden, outdoor bar, or office breakroom) simulated using 360° video projection. A series of open-ended questions elicited descriptions of product perception, similar products, and potential drivers of (dis)liking.Parallel to this, we analyzed descriptions of typical beers, seltzers, and other drink categories from 518 online survey responses with Correspondence Analysis to define a Beverage Category Space. This allowed us to calculate beer-likeness and seltzer-likeness scores for common vocabulary words. The descriptions given during immersive tasting were projected into the Beverage Category Space as supplemental variables to determine their beer-likeness and seltzer-likeness. In the bar, participants more often compared the drinks to beer, while in the breakroom, participants focused more on carbonation. Regular beer-drinkers described the products as less beer-like than regular seltzer-drinkers. These findings suggest that consumers tasting unfamiliar products may assimilate expectations cued by eating or drinking context, but experience contrast effects from expectations based on similar familiar products.

ONOMASTIC SPACE OF KAZAKH AND BASHKIR LANGUAGES

This article discusses the theory naming system of the Kazakh and Bashkir languages. The main sections of Kazakh and Bashkir onomastics are described, the degree of study of its individual sections is analyzed, according to which the course of development of Kazakh and Bashkir onomastics is determined. Although the main sections of onomastics are currently studied in detail, its individual areas still require study and systematization. In this regard, the historical materials that were guided in the study of onomastic space make it possible to identify the linguistic connection of onomastic units, show their connection with the history and culture of the people, as well as to cite the continuity of some phenomena in the formation of historical Kazakh and Bashkir names with a certain period of public life. As a result, it is established that in the basic vocabulary of Kazakh and Bashkir names, along with common Turkic words, other elements are used, and the lack of consistency in modern Kazakh surname writing, and in modern Bashkir, models of writing a person's last name (patronymic) are formed in accordance with the word-forming patterns of the Russian language, are shown on the basis of specific language data.

Bibliometric Profile of Research on Physical Activities in Special Education

The aim of the research is to understand the bibliometric profile of physical activity research in special education. The researchers first decided on the database to be searched. Then, keywords were determined and the data were converted into a form suitable for analysis. Then, data analysis was carried out. As a result of the research, a series of keywords were decided to ensure that publications containing research on physical activity in special education were included: "(AB=("special education")) AND AB=("sport" or "physical activity" or "exercise") In the first search, 255 articles were reached. After excluding the excluded articles, 137 articles were analysed. Using the restriction options of the WoS database, the search was restricted to consist only of articles and to be between 1992 and 2024. Articles and early access were selected and all languages were selected as the language of publication. VOSviewer, Microsoft Excel 2016 and the open source Biblioshiny package program created in R programming language for bibliometric analyses were used in the analysis of the research data. In this study, the number of publications was taken into account to determine the effective journals in the field, and the number of local and global citations was evaluated to determine the effective publications. In order to evaluate the historical development of research on physical activity in special education, the frequency of publication by years was used. Likewise, in order to determine the publication efficiency of the countries, the number of publications of the relevant authors according to their countries was evaluated. Common word analyses and strategic diagrams were used to identify thematic research areas.

TEACHING “LEXICOGRAPHY” IN THE 10TH GRADE OF PUBLIC SCHOOL

Our research aims at presenting several questions related to the teaching of “Lexicography” which will ensure the quality of the educational process, contributing to students’ acquisition of relevant knowledge and skills. “Lexicography” as a separate section of lexicology is concerned with the study of the types of dictionaries and the rules of creating them. The dictionary, as a reference book, defines the meaning of a word from different semantic fields and other aspects of linguistics: lexicology, semantics, etymology, stylistics. In dictionaries, words and related word units are compiled according to certain ethics and principles. Dictionaries also emphasize changes that have occurred in the meaning of words over time by serving a storehouse of common words and special terms of two or more languages in the context of translation. From this point of view, the main goal of the lexicographer is to accurately explain the meanings expressed by tens of thousands of words, their nuances, and the changes in the meaning of the word. Each lexicographer himself decides the word stock of his dictionary, the arrangement of words, the methods of explaining words.

Dissociating the Effects of Visual Similarity for Brand Names and Common Words.

Abstractionist models of visual word recognition can easily accommodate the absence of visual similarity effects in misspelled common words (e.g., viotin vs. viocin) during lexical decision tasks. However, these models fail to account for the sizable effects of visual similarity observed in misspelled brand names (e.g., anazon produces longer responses and more errors than atazon). Importantly, this dissociation has only been reported in separate experiments. Thus, a crucial experiment is necessary to simultaneously examine the role of visual similarity with misspelled common words and brand names. In the current experiment, participants performed a lexical decision task using both brand names and common words. Nonword foils were created by replacing visually similar letters (e.g., anazon [baseword: amazon], anarilllo [amarillo, yellow]) or visually dissimilar letters (e.g., atazon, atarillo). Results showed sizeable visual letter similarity effects for misspelled brand names in response times and percent error. Critically, these effects were absent for misspelled common words. The pervasiveness of visual similarity effects for misspelled brand names, even in the presence of common words, challenges purely abstractionist accounts of visual word recognition. Instead, these findings support instance-based and weakly abstractionist theories, suggesting that episodic traces in the mental lexicon may retain perceptual information, particularly when words are repeatedly presented in a similar format.

Ofer Hronrade—Defining the Long-Enigmatic “Hron” of Old English

ABSTRACT The poetic compound hronrad at the beginning of Beowulf is often translated as “whale road”, despite protestations from J.R.R. Tolkien that have hitherto been unheeded. Through an exhaustive contextual study of the Old English word hron—and its relationship with the common word hwæl—as well as statistical analysis of British marine biology, this paper seeks to demonstrate that the meaning of hron should indeed be separated from the Modern English word “whale”, with “orca” or “large dolphin” likely being more accurate translations.

Tracking the brain signature of (mis)spelled logotypes via letter transpositions and replacements

All leading models of visual word recognition assume a hierarchical process that progressively converts the visual input into abstract letter and word representations. However, the results from recent behavioral studies suggest that the mental representations of words with a highly consistent visual format, such as logotypes, may comprise not only purely abstract information but also perceptual information. This hypothesis would explain why participants often misperceive transposed-letter misspellings with the original base words to a larger degree in logotypes (e.g., SASMUNG, but not SARVUNG, is perceived as SAMSUNG) than in common words. The present experiment examined the electrophysiological signature behind the identification of correctly spelled and misspelled logotypes (via letter transposition or replacement) in an ERP go/no-go semantic categorization experiment. Results showed that N400 amplitudes for transposed-letter misspelled logotypes (SASMUNG) and intact logotypes (SAMSUNG) did not differ significantly across various time windows (until 600 ms), whereas replacement-letter misspelled logotypes (SARVUNG) yielded consistently larger N400 amplitudes. These findings reveal that the mental representations of logotypes are particularly resistant to minor orthographic changes, which has important theoretical and applied (e.g., marketing) implications.

Text Mining Analysis of Beyond Lithium-Ion Batteries

Li-ion batteries (LIBs) are the most commonly used energy storage technology in various consumer goods, including electric vehicles. However, several alternatives, so-called beyond-LIBs, are greatly investigated to decrease battery costs using abundant and globally distributed materials with high theoretical capacities. Among the diverse beyond LIB systems, this paper includes the top 6 researched chemistries: univalent (Na- and K-) and multivalent (Zn-) metal-ion, metal-air (Li-air and Zn-air), and Li-S batteries. Naturally, all these six battery chemistries have problems that must be addressed before mass commercialization. Although there are 24,523 publications on these batteries, a parallel examination of these technologies to transfer knowledge must be included in the literature. This study used text mining analysis to study the most common keywords and word connections for beyond-LIBs to learn from the general trends in the literature [1].First, the dataset was built using the Web of Science database in June 2023 by applying all the possible alternative names of beyond LIBs in the search with the Title option. Hence, the abstracts, author keywords, and keywords plus for each battery chemistry were obtained together with the article information. Afterward, data cleaning and text mining analysis were performed using the R Studio environment, specifically stringr, tm, pluralize, and tidytext libraries. The research interests in the primary battery parts and the single material-related words and two-word bigrams were investigated.The bibliometric analysis has shown that Li-S and Na-ion batteries are the most popular research areas in the beyond LIB literature. On the other hand, interestingly, Li-air batteries lost their popularity to Zn-air in around 2015. Publications on Zn-ion batteries have a sharp increasing trend, and K-ion batteries have started to share this research interest. When the single-word results are analyzed, it has been seen that anode, cathode, and electrolyte are the most commonly studied battery sections for Na- and K-ion, Zn-ion and Li-S, and finally, Zn- and Li-air batteries, respectively. Apart from the battery parts, regardless of the chemistry, the high frequency of carbon and graphene keywords are detected; hence, bigram analysis is further performed on these keywords to see the most associated words with these materials. It has been seen that carbon nanotubes are the first and nanofibers are the second preferred form of carbons, whereas the graphene oxides are found to be promising for all beyond LIBs, given only good results are reported in the literature.

THE ANALYSIS OF STRATEGIES IN TRANSLATING SWEAR WORDS IN FREE GUY MOVIE SUBTITLE

This research aims to analyze the types of swear words and translation strategies used by translators in translating swear words in Free Guy movie. The data used in this research consists of subtitles from the movie in the form of words, phrases, clauses, and sentences. The film can be accessed via Disney+Hotstar.com and was released in 2021. The research adopts a descriptive-qualitative methodology and employs Anderson and Trudgill's theory on swear word and Baker's theory on translation strategies. The results of the research indicate that a total of 85 swear words. The most frequent type of swear word is expletive swearing with 55 data (64.70%). The second most common type is abusive swearing with 15 data (17.64%). Auxiliary swearing has 9 data (10.58%), and the least frequent is humorous swearing with 6 data (7.05%). In terms of translation strategies, there are four strategies were identified. The most frequently used strategy is translation using a more neutral meaning with 34 data (40%). The second most common strategy is translation using common words with 25 data (29.41%). Translation by omission has 21 data (24.70%), and the least frequent strategy is paraphrasing using related words with 5 data (5.88%). The high occurrence of expletive swearing is attributed to the characters expressing their emotions or feelings rather than intending to intimidate, insult, or joke. The translation strategy using more neutral or less expressive words is often employed by translators when they encounter difficulties in translating the cultural context from the SL to the TL.

Bibliometric Analysis Bibliometric Analysis of Research (1980-2023)

The concept of bibliometric analysis, in addition to seeing the developments in any scientific field over a certain period of time, also provides information about where the scientific field in question will evolve in the future by offering a different perspective to understand the evolution of the field related to the concept. Bibliometric analysis method, which is used as an element or content in socio-economic fields such as communication, public relations, advertising, marketing, health, business, economy, finance and banking, technology, education, politics, etc., is the subject of many academic researches and numerous studies in the literature. The concept of bibliometric analysis is intricate and complex, and performing a bibliometric analysis of bibliometric analysis research will be able to provide a panoramic perspective to researchers and organizations in different disciplines. The research aims to evaluate the status of the concept of bibliometric analysis in the international literature within the framework of descriptive analysis with the document review method. For this purpose, after searching the Web of Science database and the necessary limitation procedures, a total of 18.432 published scientific studies published between 1980 and 2023 that include the concept of bibliometric analysis in all research, titles or keywords or have bibliometric analysis content were accessed. A total of 18.432 scientific studies accessed constitute the sample of the study. A total of 18.432 scientific studies with bibliometric analysis content were analyzed with the VOS viewer program to determine the scientific categories and interest orientation in which the interest in bibliometric analysis is concentrated, and the prominent country, organization, author and keyword concept units were reached with the publication-citation mapping technique. As a result of the research, besides the fact that the studies on bibliometric analysis are generally co-authored and that there is a high level of collaborative index in the fields of study, no common concept association related to bibliometric analysis or any common word concept or keyword association related to the expression bibliometric analysis was found.

Is being clever enough? Young people’s construction of the ideal student in computer science education

ABSTRACT Popular discourses of computing and computer science can often frame the sector and the people within it as highly intelligent yet socially challenged, contributing to stereotypes that can potentially exclude those perceived to lack these skills or characteristics. For young people, such stereotypes can influence their educational and career aspirations, especially if there are discrepancies between their own identity and perceptions of what is desirable for computer science students. Drawing on open-ended questionnaire data from 3235 young people in England (aged 11–16), we collected 9442 keywords that students used to describe their “ideal student” in computer science education. An understanding of these perceptions allows us to recognise the prevailing stereotypes that may be shaping young people’s views and aspirations. In this paper, we employ an innovative large-scale descriptive analysis of the most common words that students use to describe the ideal computer science student, including its differences, if any, by students’ demographic background (e.g. gender, ethnicity, free school meal) and responses to the questionnaire (e.g. aspirations to be a computer scientist). We tentatively identified eight clusters of popular ideal student characteristics, namely being Smart & Clever; Knowledgeable & Interested; Determined & Hardworking; Kind & Helpful; Creative; Independent; Confident; and Collaborative. By examining how students imagine the ideal student in computer science, we gain better understanding of their educational aspirations and choice of study and provide educators with valuable insights to potentially challenge and reshape these perceptions. These insights can inform educational interventions to foster a more inclusive computing education.

Lexical variation of woods and bush in Ontario English

AbstractThis paper examines ongoing lexical variability among words that describe areas with trees, such as woods, bush and forest, among others. The historical perspective shows ongoing semantic evolution of these terms, from wood(s) (c.825) to the emergence of bush in the late 16th century or early 17th century. We assess regional, social and linguistic patterns of variation in 1849 tokens, from individuals born in the late 1800s to early 200s across 21 communities in Ontario, Canada. The most common word is bush; use of woods is moderate while forest is rare. Ancestry and migration play key roles in their distribution, demonstrating that ancestral roots, migration and language contact play into the selection of a word. We argue that lexical variation, when analysed in a comparative sociolinguistic perspective in the context of social typology, history and geographic location, offers important insights into language use and human behaviour.

Attention-based RNN with question-aware loss and multi-level copying mechanism for natural answer generation

Natural answer generation is in a very clear practical significance and strong application background, which can be widely used in the field of knowledge services such as community question answering and intelligent customer service. Traditional knowledge question answering is to provide precise answer entities and neglect the defects; namely, users hope to receive a complete natural answer. In this research, we propose a novel attention-based recurrent neural network for natural answer generation, which is enhanced with multi-level copying mechanisms and question-aware loss. To generate natural answers that conform to grammar, we leverage multi-level copying mechanisms and the prediction mechanism which can copy semantic units and predict common words. Moreover, considering the problem that the generated natural answer does not match the user question, question-aware loss is introduced to make the generated target answer sequences correspond to the question. Experiments on three response generation tasks show our model to be superior in quality while being more parallelizable and requiring significantly less time to train. Our model achieves 0.727 BLEU on the SimpleQuestions response generation task, improving over the existing best results by over 0.007 BLEU. Our model has scored a significant enhancement on naturalness with up to 0.05 more than best performing baseline. The simulation results show that our method can generate grammatical and contextual natural answers according to user needs.

Thematic modeling and linguistic analysis of text messages from a social network for information and analytical support of logistics business

In the modern economy, the success of a business is largely determined by the company’s ability to analyze consumer preferences, consumer attitudes towards the company’s products, as well as the ability to quickly respond to changing preferences or negative trends. Social listening is a technology for analyzing conversations, text messages and any kind of mention of a company, its products or brand. Currently, it is most effective to carry out social listening by monitoring social networks (VKontakte, etc.), which are the largest sources of text messages from millions of users. The purpose of this work is to analyze the practices of using social listening technology, as well as common approaches to the use of social networks by domestic and foreign companies. Based on the specialized software developed by the authors, an analysis of more than 50 000 news reports published in 2021–2024 was carried out on companies of different levels and specialization. Using linguistic analysis of the corpus of text messages for various companies and sectors of the economy, the most common words were identified, thematic modeling was carried out, and the dynamics of news reports and their relationship with external factors were studied.

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.

The names of outerwear in the Tatar and Chuvash languages

This work studies the vocabulary of outerwear in two related Turkic languages – Tatar and Chuvash. These two languages of neighboring peoples closely interact, which leads to their interpenetration, including the linguistic elements.In the article, Tatar and Chuvash lexemes, included in the thematic group “outerwear”, are analyzed in a comparative aspect. The words are considered in historical and etymological terms. The work provides examples from other Turkic languages and investigates the borrowing of these words into the Russian language.The article concludes that the stem of lexemes expressing the meaning of outerwear is made up of common Turkic words such as chikmen, tolyp, kurk, chapan, ermek, tun, bishmet, etc., although researchers believe some of them to be borrowings from other languages. Some of the words were borrowed into the Chuvash language from Tatar: sapan, kamsul, beshmet, etc. The etymology of such foreign words as kamsul is generally believed to come from Italian through Russian, zybyn, choba from Arabic, etc. Some names of outerwear were adopted into the Russian language from Turkic languages: beshmet, azyam, armyak, chekmen, epancha, kaftan, tulup, chapan, etc. The fact that the origin of many words is determined by scientists in different ways makes their study more complicated.

Subtitling Strategies of Buya Hamka Vol.1 Movie and Its Implication for Teaching Translation

The existences of subtitling (a part of audiovisual translation) in assisting people from other countries to enjoy movies have been new breakthroughs yet challenges to film industries. Nowadays, many Indonesian movies present the richness of local languages such as Javanese language, Minangkabau language, Batak language, and other local languages accompanied by English subtitles, so the movies can be watched not only by Indonesian audiences, but also viewers from other countries. One of the movies is Buya Hamka Vol.1 movie. This study aims to reveal the subtitling strategies used in Buya Hamka Vol.1 movie and its implication to teaching translation. This was a qualitative study with content analysis design. The data were the excerpts of conversations using Minangkabaunese (source language) compared to the correspond English (target language) subtitle provided by Netflix, and were analysed by using subtitling strategies theory by Gottlieb. The result showed that transfer is the most frequently strategy found in the study because of the common word order pattern employed in Minangkabaunese and English.