Word Selection Research Articles

Al_Muhibi Methodology and Interests through the Book, (Khulasat Al'athar Fi A'aeyan Alkarn AL-Hadi Ashar)

This study tackles the historical methodology of Al_Muhibi in his book (Kulaste AL'ather), It also aims at shedding light on his very distinguished methodology through the book Kulaste AL'ather, and his book is one of the most important translation books of that period. The results indicated that Al_Muhibi followed in his translation his own style and he was very careful in the selection of words to maintain the meaning, and he chose rhetorical methods, and he was out of the content of the comprehensiveness of the translations, to confine them in a period of time which is chronologically near.

Emergency Risk Communication

The ongoing coronavirus outbreak has caused a public health emergency of international concern. During public health emergencies, effective risk communication plays an indispensable part in a country’s emergency response. This paper explores the use of Structural Topic Modelling, a machine learning technique that automatically identifies key topics and their content in textual data, in analysing emergency risk communication (ERC) practice at the state level. The data is from the UK government’s COVID-19 press briefings televised between March 2020 and June 2021, totalling approximately 1 million words. The study identifies the prominent topics covered in those briefings as well as their distribution over time, which in turn reflect the UK government’s priorities in handling the public health emergency. Close scrutiny of the use of a selection of key words in context sheds further light on the government’s ERC practice from a linguistic point of view.

Writing Strategy: an Analysis of Successful Malahayati English Council Learners in Writing

Writing Strategy: an Analysis Of Successful Malahayati English Council Learners in Writing. The purpose of this study is to discover what kinds of learning strategies are used by successful learners to improve their English writing skills. This study employed an explanatory mixed method. A questionnaire is an instrument used to collect data. The population in this study was Malahayati English Council students enrolled in writing classes, and the sample consisted of students who earned an A (86-100) in the final writing subject. The data was analyzed using a simple statistic and the cumulative frequency distribution method. Based on the result of this study, it was concluded that first, Writing is a continuous process of thinking, organizing, rethinking, and reorganizing. It requires command of vocabulary, spelling, grammar, punctuation, appropriate content, and word selection for the audience, topic, and occasion. A writer must be able to think and express ideas in well-organized sentences with high coherence. Second, successful learners applied the writing strategies those are suggested by the expert. They used those strategies to solve all problems and to get the best results in writing. Third, the strategy employed is to divide the writing process into four stages: prewriting, drafting, revising, and editing

Comparative Analysis of Ideational Metafunction between Presenters in Talk Show

This study aims to examine the similarities and differences of meaning in language style used ideational metafunction in Kick Andy and Mata Najwa talk show. The purpose of this research is to find similarities and differences of in meaning language style used ideational metafunction of Matthiessen (2014). The object of this research are Kick Andy and Mata Najwa talk show videos from Youtube channel. The method of this research uses descriptive qualitative research. The result of this research show two similarities and four differences in level ideational metafunction. The conclusion of this study there are more differences rather then similarities, because the differences in style are affected by different gender which are presented through lead and speech to the different ways of selection and producing of word in the ideational of metafunction.

ANALISIS KESALAHAAN EJAAN TERHADAP TEKS BERITA “BIKIN GAGAL GINJAL, ETILEN GLIKOL DI OBAT SIRUP TERNYATA ‘FAMILIAR’ DI MESIN” PADA MEDIA ONLINE DETIKOTO”

In online media, writing errors regarding language are often found. One of them is online media in the process of writing news texts sometimes in a hurry because it is based on a predetermined deadline. This error occurs because it violates two of the three terms of word selection, namely "true" and "right". This study aims to (1) describe the form of language errors in terms of the use of word choice and italics contained in the DetikOto online news text, (2) explain the form of errors and language corrections in terms of the use of word choice and italics that dominantly appear in news texts. online detikOto. This research uses a descriptive method. The data of this research are in the form of errors in words and sentences containing language errors in the DetikOto news text. Data collection techniques used are reading, marking errors, identifying, analyzing, and concluding. While the instrument in this study is the researcher himself and the instructions for errors and improvements. Furthermore, the note-taking technique is used to write down the problems in the reading. The note-taking technique used is to record words or sentences which are a form of language error in the field of spelling. After being analyzed and described based on the form of language errors in the field of spelling, errors in spelling in the news text include: 1. Word Choice Errors, 2. Acronym Errors, 3. Title Writing, 4. Italicized Writing. Then concluded from the improvement of the sentence.

Combining GCN and Transformer for Chinese Grammatical Error Detection

<p>This paper describes our system at a task: Chinese Grammatical Error Diagnosis (CGED). The task is held by the Natural Language Processing Techniques for Educational Applications (NLP-TEA) to encourage the development of automatic grammatical error diagnosis in Chinese learning since 2014. The goal of CGED is to diagnose four types of grammatical errors: word selection (S), redundant words (R), missing words (M), and disordered words (W). The automatic CGED system contains two parts including error detection and error correction and our system is designed to solve the error detection problem. Our system is built on three models: 1) a BERT-based model leveraging syntactic information; 2) a BERT-based model leveraging contextual embeddings; 3) a lexicon-based graph neural network leveraging lexical information. We also design an ensemble mechanism to improve the single model’s performance. Finally, our system achieves the highest F1 scores at detection level and identification level among all teams participating in the CGED 2020 task.</p> <p> </p>

Archaisms in the proverb «Basy – bapan, ayagi – sapan»

The problem of dynamic changes in the vocabulary of the Kazakh language has become particularly relevant in recent years. Many researchers note that a deep and comprehensive study of obsolete words is of undoubted interest, since these words affect the development of the vocabulary of the language. The language, which is constantly updated with new words, also refuses words that have become unnecessary for certain reasons. And what keeps these words in the language-proverbs and sayings, phraseological units. They are similar to sarcophagi for obsolete words. This article analyzes the obsolete words «bapan» and «sapan», preserved in the proverb «Basy – bapan, ayagi – sapan». In Kazakh linguistics, opinions about the meaning and etymology of these words are erroneous. As a result of the language analysis, it was determined that the word «bapan» is the fluffy top of the reed, and the word «sapan» is the stem of the reed. The data of the Kazakh language is compared with the data of the Kyrgyz and other Turkic languages. The aim of the study is to show the effectiveness of the research in the context, and not in the individual selection of obsolete words in the composition of proverbs and sayings. In accordance with this goal, an attempt was made to determine the origin and meaning of obsolete words in this proverb. Keywords: archaisms, proverbs, sayings, etymology, paremiology.

Teaching Reading According to Selective Word Clusters among Children with Dyslexia

The problem of not acquiring reading skills is often debated in the education world. The purpose of this study was to develop framework with selective word clusters among children with dyslexia. This study employed survey as its research method. The findings showed that there was no significant difference by gender with t-value = -1.26, p = .211 (p> .05) on teaching reading using selective word clusters for children with dyslexia by gender. The findings also showed there is no significant difference on teaching reading using interactive learning materials for children with dyslexia based on gender with a value of t = 1.24, p = .222 (p> .05). The result of the Pearson correlation test on teaching reading using selective word clusters and interactive learning materials shows a significant r value = .403 ** (p <.005). By drawing on evidence from the data, we proposed framework for children with dyslexia which included three major word clusters. We also argue that to overcome the problems associated with reading difficulties, we need to take into account the selection of appropriate words as one of the foremost factors. We conclude that this research outcomes will allow for a richer understanding of learning to read among children with dyslexia. This lays a solid foundation for pedagogic developmental efforts by using mobile application in reading activities.

토픽모델링 분석을 이용한 학습역량 연구 동향 분석 및 대학 학습지원 방향 모색

Objectives Universities have expanded various support to strengthen students' learning capabilities. However, the meaning and interpretation of learning capabilities were diverse and ambiguous, causing uncertainty in deriving directions for setting learning support goals and establishing promotion strategies. Recognizing these problems, this study aims to prepare evidence for establishing a university learning support system by analyzing trends in studies related to learning competency and extracting topics related to learning competency through text mining and network analysis.&#x0D; Methods Basic statistical analysis, core word selection, topic extraction, and research trend were analyzed using keyword network analysis and LDA-based topic modeling techniques by collecting information on the titles and abstracts of 621 academic papers on learning competencies.&#x0D; Results The keywords related to learning competency were groups, and the results of selecting key words were learning immersion, self-efficacy, self-regulated learning ability, learning community, problem-solving ability, cooperative learning, knowledge, and creativity. As a result of topic modeling, five topics were extracted, and they were named as learning motivation, learning analysis, learning execution, learning relationship, and learning expansion. Next, as a result of analysis of research trends related to learning competency, it was found that research on learning competency has continued to increase since 2010, and research on learning relationships and learning expansion topics has increased since 2015.&#x0D; Conclusions This study is meaningful in that it identified the keywords mentioned in current learning-related studies to foster future talent, extracted and presented related topics, and presented basic data on finding effective support directions to improve student learning competency in universities.

Perceptions and imaginaries about the fourth industrial revolution between geographies of opportunity and discontent: Some reflections on the Italian case

AbstractThe pervasiveness of advanced technologies and their disruptive impact on society have spurred the debate on the emergence of a new industrial revolution and on its positive and negative effects, both at an individual and spatial level. This paper aims to contribute to this debate, focusing attention on the perception of changes related to the Fourth Industrial Revolution and exploring new methods of analysis of the manifestations of both techno‐enthusiasm and opposition to it. Starting from the extensive literature in this field, the work adopts two research perspectives: the study of imaginaries and narratives developed around the Fourth Industrial Revolution, which convey different messages from social groups and places; the geographies of opportunity and discontent, which address the resentment expressed by some localities towards advanced technological models and growing inequalities. In this work the Fourth Industrial Revolution is not interpreted through data about the technological variables or interviews to protagonists of the phenomenon; rather, emphasis is on the points of view of non‐institutional subjects and, in particular, the opinions expressed by people on the Web. For this reason, the sentiment analysis has been adopted to identify both positive and negative polarities and the relevance of specific feelings through the selection of key words related to the notion of the Fourth Industrial Revolution. The empirical analysis based on this methodology focuses on the Italian case in a specific period (first and second phase of the pandemic, from January 2020 to September 2021) and, at a local level, on the comparison between four medium‐sized cities (Pisa, Lecce, Taranto and Terni). This paper also tries to extend recent contributions through the provision of new perspectives for the definition of policies designed with the involvement of the population and places regarding both the processes of technological change and the definition of new socio‐spatial models.

ACapMed: Automatic Captioning for Medical Imaging

Medical image captioning is a very challenging task that has been rarely addressed in the literature on natural image captioning. Some existing image captioning techniques exploit objects present in the image next to the visual features while generating descriptions. However, this is not possible for medical image captioning when one requires following clinician-like explanations in image content descriptions. Inspired by the preceding, this paper proposes using medical concepts associated with images, in accordance with their visual features, to generate new captions. Our end-to-end trainable network is composed of a semantic feature encoder based on a multi-label classifier to identify medical concepts related to images, a visual feature encoder, and an LSTM model for text generation. Beam search is employed to ensure the best selection of the next word for a given sequence of words based on the merged features of the medical image. We evaluated our proposal on the ImageCLEF medical captioning dataset, and the results demonstrate the effectiveness and efficiency of the developed approach.

A rule-based/BPSO approach to produce low-dimensional semantic basis vectors set

The present study aims to generate low-dimensional explicit distributional semantic vectors. In explicit semantic vectors, each dimension corresponds to a word, which makes word vectors interpretable. In this study, a new approach is proposed to obtain low-dimensional explicit semantic vectors. Firstly, the suggested approach considers three criteria, namely, word similarity, number of zeros, and word frequency as features for words in a corpus. Next, some rules are extracted to obtain the initial basis words using a decision tree which is drawn based on the three features. Secondly, a binary weighting method is proposed based on the binary particle swarm optimization algorithm which obtains NB = 1000 context words. In addition, a word selection method is used to provide NS = 1000 context words. Thirdly, the golden words of the corpus are extracted based on the binary weighting method. Subsequently, the extracted golden words are added to the context words which are selected by the word selection method as the golden context words. The ukWaC corpus is utilized for constructing the word vectors. MEN, RG-65, and SimLex-999 test sets are used to evaluate the word vectors. Next, the results are compared to a baseline which uses 5K most frequent words in the corpus as the context words. The baseline method uses a fixed window to count the cooccurrences. The word vectors are obtained using the 1000 selected context words along with the golden context words. Compared to the baseline method, the suggested approach can increase Spearman?s correlation coefficient for the MEN, RG-65, and SimLex-999 test sets by 4.66%, 14.73%, and 1.08%, respectively.

SPEECH CHARACTERISTICS AND METHODS OF ITS TRANSLATION

Background. The article is devoted to the study of ways to transfer the features of the character’s speech characteristics into Russian. The authors consider speech characterization as a selection of words, expressions and turns of speech, acting as a means of artistic representation of actors. The functions that perform the speech features of the character are discussed in the work. The authors analyze the ways of translating the speech characteristics of the characters of D. Mitchell’s work Black Swan Green into Russian, comparing two existing translations by T. Borovikova and A. Polyarinov.&#x0D; Purpose. To identify ways of translating the speech characteristics of the characters by the example of translations of the work of D. Mitchell Black Swan Green, performed by T. Borovikova and A. Polyarinov.&#x0D; Materials and methods. The material of the research is David Mitchell’s novel Black Swan Green, as well as its translations into Russian, made by Tatiana Borovikova and Alexey Polyarinov. The research methods were the comparative analysis, linguistic observation, as well as the continuous sampling method.&#x0D; Results. Based on the analysis of fragments from the work, it was revealed that when translating the speech characteristics of the characters, the translators used lexical and grammatical transformations (functional replacements, omissions, literal translation, repetition and doubling of the consonant sound, concretization and addition), trying to preserve both the plan of expression and the plan of content.

A Cross-Sectional Study of Textese in Academic Writing: Magnitude of Penetration, Impacts, and Perceptions

This cross-sectional study examined the distribution of electronic texting patterns in academic writing and effects of textese on EFL learners’ writing performance. It also explored teachers’ perspectives on this phenomenon. Data were gleaned from 60 undergraduates enrolled for a license degree in English language and literature and 10 of their professors who were familiar with writing skills of this body of informants. A corpus of texts derived from exam scripts, assignments, and lecture notes was analyzed, and the teachers were interviewed. The results revealed that learners tend to transfer some patterns of instant messaging (IM) into their writing. However, this remains rather limited to morphosyntactic features and some other paralinguistic features and local-based contents. The phenomenon was pervasive across the sample in a descending order; learners at the entry level e-texted more than their seniors did. Besides, heavy texters used this deformed variety of English to compensate low writing proficiency in terms of spelling, word selection, and sentence structures. Additionally, texting was apparently evident in note-taking more than in answer sheets and assignments. The study concludes that textese is not a surrogate for the Standard English but an addition to it with a variance of scope and purpose of usage.

Tone in UNICEF Press Releases in the Global Settings: A Contrastive Analysis

Tone sets the readers' mood in which the writers confide their writing styles which can convey much of the cultural background of the community to where they belong. In the world's preceding advancement, the tone in a text has limited literature in the field. This motivated the researcher to look at the press release as it is the new face of public relations. The nature of the study is on Intercultural rhetoric (IR)/Contrastive Rhetoric (CR), the study of written discourse between and among individuals with different cultural backgrounds. The study used quantitative and qualitative approaches as they complement the richness of the study. The gathered press release headlines of UNICEF written by authors from varied discourse communities, namely the Philippines, Thailand, and the United States of America, had gone through content analysis and discovered the ingenuity and inspiration in their word selection in writing headlines. The headlines from the Philippines are analyzed for having a committed tone and logical and analytical attitude. Interestingly, press releases from Thailand have a committed tone as well. On the other hand, press releases from the USA have a neutral tone.

Struktur Lirik Lagu dalam Album Cidro Asmoro Kajian Strukturalisme

This research was written with the aim to determine the lyric structure of the song in the album Cidro Asmoro using the study of Structuralism. The structure in the lyrics of this song consists of physical structure and inner structure. Physical structure is the structure of the builder of a poem that is physical or fit in the form of word order. While the inner structure is the structure of the poet builder from within or contains the meaning that the author wants to express. The research method used to analyze the physical structure and the inner structure uses a qualitative descriptive method. The data used in this study are words, phrases, and sentences in the lyrics of the song Cidro Asmoro that refer to the structure of the builder. The results found in this study is that there is a physical structure in the form of majas, recitation, diction, concrete words and rhyme in the lyrics of songs in the album Cidro Asmoro. Majas or language styles found include majas personification, metaphor, association, allegory and hyperbole. In addition, also found imagery or imagery in the form of imagery of sight, hearing, taste, touch and movement. The inner structure in the lyrics of Cidro Asmoro's album has themes, tastes, tones and messages. Selection of lyrics and words from Cidro Asmoro's album has a unique characteristic to convey the feelings experienced by the author. This feeling can be from love, disappointment, confusion, anger and even enthusiasm. Cidro Asmoro's album contains the story of a man's love struggle who ultimately has to give up his lover with another man.

Aliasing black box adversarial attack with joint self-attention distribution and confidence probability

Deep neural networks (DNNs) are vulnerable to adversarial attacks, in which a small perturbation to samples can cause misclassification. However, how to select important words for textual attack models is a big challenge. Therefore, in this paper, an innovative score-based attack model is proposed to solve the important words selection problem for textual attack models. To this end, the generation of semantically adversarial examples in this model is adopted to mislead a text classification model. Then, this model integrates the self-attention mechanism and confidence probabilities for the selection of the important words. Moreover, an alternative model similar to the transfer attack is introduced to reflect the correlation degree of words inside the texts. Finally, adversarial training experimental results demonstrate the superiority of the proposed model.

Standardized item selection for alternate computerized versions of Rey Auditory Verbal Learning Test(-based) word lists

ABSTRACT Introduction Despite an increasing need for new Rey Auditory Verbal Learning Test (RAVLT)-based word lists in computerized testing, no criteria or standardized procedures exist for its development. To lay a foundation for future development of new and alternate computerized RAVLT(-based) word lists, we present cross-lingual word criteria, developed new lists using the criteria and evaluated performance on the lists using online assessment. Method Based on psycholinguistic literature, we identified relevant word selection criteria. To validate the criteria, we developed two new American-English word lists and one new Dutch list, and administered the RAVLT using visual presentation of the new or original list in an online American (n = 248) and Dutch sample (n = 246) of healthy people. We compared performance of the new and original word lists on trial scores and serial position effects using Bayesian correlations and analyses of variance. Additionally, we compared proportions of correct responses per item, corrected for serial position. Results We identified 13 relevant word selection criteria. The criteria led to two new highly comparable American-English word lists with lower trial scores compared to the original American-English list, indicating that the criteria helped to develop parallel lists with fewer associations between items. The new Dutch word list showed similar trial scores, serial position effects, and proportions of correct responses per item corrected for serial position compared to the original Dutch version. Conclusions The systematic use of word selection criteria can facilitate development of new parallel word lists, including in new language areas. Future studies should evaluate the use of the word criteria for the other sections of the RAVLT (such as delayed recall and recognition), performance using original test modalities (auditory presentation and recall of words) as well as performance in clinical samples.

Correlation of Narrative Evaluations to Clerkship Grades Using Statistical Sentiment Analysis.

Narrative evaluations are essential components of medical student assessment. This study evaluated how well narrative clerkship evaluation word choice correlated with an assigned letter grade. One hundred clerkship evaluations, 50 from family medicine (FM) and 50 from internal medicine (IM), with even distribution of "Honors" and "Near-Honors" among medical students that graduated in 2020 from the Oregon Health and Science University (OHSU) were examined. A textual sentiment analysis, which evaluates positive and negative word choice, was used to determine each evaluation's collective sentiment. An average sentiment score and character count were calculated for Honors and Near-Honors evaluations from both clerkship disciplines. Sentiment word totals were used to form "word clouds" that highlight the most frequent word selections. While sentiment scores positively correlated with the assigned grade, there was no statistically significant difference between the average sentiment scores among Honors and Near Honors graded evaluations within the FM or IM clerkship evaluation sets. There was no significant difference in evaluation character length among the assigned grades. Among FM evaluations, "outstanding" and "excellent" were the two most common sentiment words used in both Honors and Near-Honors. Among IM evaluations, outstanding and excellent were most commonly used in Honors evaluations, while "excellent" and "good" were most common in Near-Honors. This study outlines a novel text analysis method for analyzing narrative evaluation association with assigned grade that other institutions can utilize. Sentiment word choices are not significantly different among Honors and Near Honors clerkship narrative evaluations. The online version contains supplementary material available at 10.1007/s40670-022-01654-2.

The Long Slog Through the Virtual Swamp: Making a Wetland Podcast in Spanish

The Long Slog Through the Virtual Swamp: Making a Wetland Podcast in Spanish