Dictionary Of Words Research Articles

Comparison of text information from information sources based on the cosine similarity algorithm

This article presents research aimed at developing an optimal concept of analysis and comparison of information sources based on large volumes of textual information using natural language processing (NLP) methods. The object of the study was Telegram news channels, which are used as sources of text data. Texts were pre-processed, including cleaning, tokenization, and lemmatization, to form a global dictionary consisting of unique words from all information sources. For each source, a vector representation of the texts was built, the dimension of which corresponds to the number of unique words in the global dictionary. The frequency of use of each word in the channel's texts was displayed in the corresponding positions of the vector. By applying the cosine similarity algorithm to pairs of vectors, a square matrix was obtained that demonstrates the degree of similarity between different sources. The results of the study show the effectiveness of the proposed approach for quantitative assessment of the similarity of textual data from different sources. The need for further optimization of the algorithm was identified, in particular by parameterization to achieve a balance between accuracy and computational cost, as well as the separation of words with excessive weight, such as specific terms or channel names. The proposed method can be applied to the analysis of information flows, the identification of relationships between sources and the study of the socio-cultural influence of media content in the conditions of the modern information environment.

Efficient incremental training using a novel NMT-SMT hybrid framework for translation of low-resource languages.

The data-hungry statistical machine translation (SMT) and neural machine translation (NMT) models offer state-of-the-art results for languages with abundant data resources. However, extensive research is imperative to make these models perform equally well for low-resource languages. This paper proposes a novel approach to integrate the best features of the NMT and SMT systems for improved translation performance of low-resource English-Tamil language pair. The suboptimal NMT model trained with the small parallel corpus translates the monolingual corpus and selects only the best translations, to retrain itself in the next iteration. The proposed method employs the SMT phrase-pair table to determine the best translations, based on the maximum match between the words of the phrase-pair dictionary and each of the individual translations. This repeating cycle of translation and retraining generates a large quasi-parallel corpus, thus making the NMT model more powerful. SMT-integrated incremental training demonstrates a substantial difference in translation performance as compared to the existing approaches for incremental training. The model is strengthened further by adopting a beam search decoding strategy to produce k best possible translations for each input sentence. Empirical findings prove that the proposed model with BLEU scores of 19.56 and 23.49 outperforms the baseline NMT with scores 11.06 and 17.06 for Eng-to-Tam and Tam-to-Eng translations, respectively. METEOR score evaluation further corroborates these results, proving the supremacy of the proposed model.

“My Mom Is a Fighter”: A Qualitative Analysis of the Use of Combat Metaphors in ICU Clinician Notes

BackgroundA metaphor conceptualizes one, typically abstract, experience in terms of another, more concrete, experience with the goal of making it easier to understand. Even though combat metaphors have been well-described in some health contexts, they have not been well-characterized in the setting of critical illness. Research QuestionHow do clinicians use combat metaphors when describing critically ill patients and families in the electronic health record? Study Design and MethodsWe included notes written about patients >=18 years admitted to ICUs within a large hospital system from 2012-2020. We developed a lexicon of combat words, and isolated note segments that contained any combat mentions. Combat mentions were systematically defined as a metaphor or not across two coders. Among combat metaphors, we used a grounded theory approach to construct a conceptual framework around their use. ResultsAcross 6,404 combat-related mentions, 5,970 were defined as metaphors (Cohen’s kappa 0.84). The most common metaphors were “bout” (26.2% of isolated segments), “combat” (18.5%), “confront” (17.8%) and “struggle” (17.5%). We present a conceptual framework highlighting how combat metaphors can present as identity (“mom is a fighter”) and process constructs (“struggling to breathe”). Identity constructs were usually framed around: (1) hope, (2) internal strength, and/or (3) contextualization of current illness based on prior experiences. Process constructs were used to describe: (1) “fighting for” (e.g. working toward) a goal, (2) “fighting against” an unwanted force, or (3) experiencing internal turmoil. InterpretationWe provide a novel conceptual framework around the use of combat metaphors in the ICU. Further studies are needed to understand intentionality behind their use and how they impact clinician behaviors and patient/caregiver emotional responses.

Applications of NLP to Human Resource Management: From Word Dictionaries to Large Language Models

Applications of NLP to Human Resource Management: From Word Dictionaries to Large Language Models

The economics of L2 English. Evidence from 2.0 mln subjects suggests an economics of language framework to account for country differences in L2 English proficiency

ABSTRACT We analysed Education First’s Standard English Test scores coming from 2 mln learners of English in 109 countries world-wide. Proficiency in English as a global lingual franca is an important skill in various areas of international communication. A larger linguistic distance between English as a second language and a learner’s first language has been put forward as increasing the efforts or costs of learning English. Instead of the subjective measures used in the past, we constructed a quantitative linguistic distance measure based on comparing words (lexicon), constructions (morpho-syntax), and sounds (phonology) between English and 59 mother tongues. Mixed regression analyses were carried out on the countries’ proficiency scores with a country’s human capital index, the official status of English in a country, and linguistic distance as predictors. All three predictors turn out to be robust proficiency determinants. Language skills constitute an essential component of human resources in today’s emerging and growing knowledge economy. These skills cannot be taken for granted and additional language training is required when linguistic distances are large.

Analysis of the presentation of compound words in Korean dictionaries - Focusing on ""X+2l"" compound words from Pyojun Korean Dictionary

Analysis of the presentation of compound words in Korean dictionaries - Focusing on ""X+2l"" compound words from Pyojun Korean Dictionary

Інноваційні процеси творення аксіологійних значень в українській лінгвокультурі: проєкція на антропоніми та їхні похід

Some changes connected with sociolinguistic factors, in particular, the Russian-Ukrainian war, that are taking place in the Ukrainian vocabulary are characterized. The trends of rethinking anthroponyms and their derivatives, which, thanks to the linguistic creativity of Ukrainians, are widespread in modern Ukrainian media discourse and recorded in dictionaries of new words and meanings, as carriers of evaluatively marked meanings and senses, are highlighted. The lexical structure of the Ukrainian language is being updated on the basis of the innovative word formation processes system.

Anatomy of sovereign yield behaviour using textual news

While the relationship between the information content of macroeconomic news and the behavior of asset prices has been studied extensively in the finance literature, this study provides a new perspective by examining the impact of textual news on sovereign bond yield spreads in an emerging country. This study used bond market news published in newspapers to develop the sentiment scores using a modified word dictionary to unravel news characteristics. A nonlinear regime-shifting regression model of Markov Regime Shifting (MRS) is used to understand the impact of news on sovereign bond yield spreads. The paper results show that textual news sentiment may explain both steepening and flattening of the yield curve, with monetary and fiscal policy news having the most significant impact on yield spread behaviour. The results hold key implications for policymakers, debt fund managers and other market participants.

Pathos in Natural Language Argumentation: Emotional Appeals and Reactions

In this paper, we present a model of pathos, delineate its operationalisation, and demonstrate its utility through an analysis of natural language argumentation. We understand pathos as an interactional persuasive process in which speakers are performing pathos appeals and the audience experiences emotional reactions. We analyse two strategies of such appeals in pre-election debates: pathotic Argument Schemes based on the taxonomy proposed by Walton et al. (Argumentation schemes, Cambridge University Press, Cambridge, 2008), and emotion-eliciting language based on psychological lexicons of emotive words (Wierzba in Behav Res Methods 54:2146–2161, 2021). In order to match the appeals with possible reactions, we collect real-time social media reactions to the debates and apply sentiment analysis (Alswaidan and Menai in Knowl Inf Syst 62:2937–2987, 2020) method to observe emotion expressed in language. The results point to the importance of pathos analysis in modern discourse: speakers in political debates refer to emotions in most of their arguments, and the audience in social media reacts to those appeals using emotion-expressing language. Our results show that pathos is a common strategy in natural language argumentation which can be analysed with the support of computational methods.

Narrative Emotions and Market Crises

Robert Shiller highlights the role popular stories play in driving economic behavior and argues the need to analyze these scientifically. However, their impacts are difficult to measure directly and often conflict. We show the strength of such stories resides in the emotions they generate, and that the tenor and persuasiveness of financial narratives and their association with the market can be empirically quantified. Specifically, we textually analyze financial media reports to identify the different powerful investor emotions manifest during three recent extreme market periods, dot.com mania, the Global Financial Crisis and the COVID-19 pandemic, constructing original context-specific emotion word dictionaries for this purpose. We find investor emotions are associated with up to 52% of market returns and 67% of market uncertainty during these market crises, and provide general evidence that investor emotional dynamics may be time and context invariant.

Cultural values and the P-O fit: comparative NLP analysis of German online job advertisements

PurposeWithin the Person-Organization fit framework and Signalling Theory, this study investigates the performance of word dictionaries detecting cultural values in online job advertisements as one form of external communication of an organization. Based upon a merge of the dictionaries, a corporate value analysis of Germany is conducted.Design/methodology/approachThe study builds on a dataset (n > 151 k) of online job advertisements which were scraped from a German job portal. It was pre-processed according to natural language processing standards. For analysing the values of an organization a dictionary based word count was applied. Therefore, the current state-of-the-art dictionaries were tested, and an enhanced dictionary was developed and translated from English to German. Finally, a cluster analysis was conducted.FindingsThis study supports the possibility of measuring cultural values in texts where the enhanced dictionary based on Ponitzovskiy shows the best results. It thereby supports the use of the Universal Value Structure model (Schwartz, 1992) as well as the Signalling Theory (Guest et al., 2021), that values spread across 10 core or 4 aggregated dimensions are communicated via online job advertisements. Finally, the study offers a profile of the German corporate culture average as well as 4 cultural clusters and separate organizations, all with different profiles.Originality/valueThis study develops an enhanced dictionary based on a large dataset of online job advertisements for analysing the external communication of values or culture of an organization for improving the Person-Organization fit.

Definitions of Suffixed Loanwords in Dictionaries of Foreign Words in Slovak

Abstract Dictionaries of foreign words in Slovak have a tradition of publication that can be traced for more than one hundred years. Their popularity among users is closely connected to a general interest in so-called language cultivation, which includes a good knowledge of frequently used words of non-native origin. Here, special attention will be paid to suffixed loanwords. In the case of larger sets of loanwords with the same suffix, speakers recognize their similarity and regularity. The central aim of this paper is to investigate how the lexicographic representation of suffixed loanwords in Slovak dictionaries of foreign words developed in the past one hundred years. The analysis focuses on a set of loanwords with three non-native suffixes, namely -ácia (‘-ation’), -izmus (‘-ism’), and -ita (‘-ity’), each of which stands in competition with a corresponding native suffix. It was investigated how the emergence of a competing variant with a native suffix attached to the same foreign base influences the information given by dictionaries. For the analysis, I used five dictionaries of foreign words in Slovak published between 1939 and 2005. Based on a sample of entries from these dictionaries, I distinguish four types of dictionary definitions used to describe suffixed loanwords. Then I propose a model explaining the historical and logical relationships between these four definition types.

Association Between Young Chinese Children’s Early Writing Skills and the Chinese Preschool Classroom Writing Environment

ABSTRACT This study describes the early writing environments of 16 preschool classrooms in China and 155 Chinese preschoolers’ early writing skills as assessed through name writing, word dictation, and early composing tasks. The classroom early writing environment consists of children’s accessibility to writing materials, and teachers’ writing instruction. Preschool writing samples were coded for children’s ability to generate both oral (e.g. number of words and ideas) and written language (e.g. recognizable Chinese characters). Confirmatory factor analyses and hierarchical linear modeling were conducted to investigate the structure of Chinese preschoolers’ writing skill and to examine its association with classroom writing environment. Research Findings: Results showed that Chinese preschool children could independently generate a variety of writing samples without adult support. Early Chinese writing skills represent two factors, namely (a) the ability to transcribe recognizable characters (transcription skill), and (b) the ability to generate meaningful ideas (composing skill). Teachers’ writing instruction was significantly associated with children’s writing skill, although the frequency was low. Practice or Policy: The findings revealed the evident complexities of Chinese orthography, while suggesting a universal impact of teachers’ scaffolding to young children’s early writing. The study prepared an evidence base for future classroom-based early literacy intervention programs.

Types of Chinese loanwords and their ways of translation into Russian

Foreign loanwords are one of the sources of replenishment of the vocabulary of any language. Words of foreign languages make up a significant proportion of Chinese neologisms. The purpose of this study is to classify borrowings in modern Chinese and briefly discuss the methods of their translation into Russian. The object of this article is loanwords in Chinese neologisms based on dictionary materials, and the subject of this work is the types of Chinese loanwords. The material selected for this article is based on the dictionary of "Chinese-Russian dictionary of new words and expressions". This article briefly analyzes the classification of Chinese loanwords, split into three categories: phonetic, semantic and phonetic-semantic loanwords. Then summarizes their main methods of translation using examples. The following methods were used in the work: random selection, descriptive, contextual and transformational analysis. The component analysis method was used to analyze individual words in the text. In conclusion, the types of loanwords from the dictionary since the XXI century are analyzed and the results obtained are summarized. It is shown that when translating Chinese borrowings into Russian, transcription, transliteration, lexico-semantic substitutions, and explication of these four translation methods can be mainly used. The scientific novelty of this article lies in the fact that, based on the analysis of specific examples, it systematizes three types of Chinese loanwords and discusses letter loanwords unique to the Chinese language, which enriches the current results of the study of Chinese loanwords. On the other hand, with the development of time and the constant appearance of new words, the need to translate new Chinese vocabulary into other languages has become acute. This article attempts to provide some reference value to the Russian translation of Chinese loanwords.

A Study on the Semantics of the Sichuan Dialect Word Ba Based on the Cognitive Perspective

The Sichuan dialect word ba is widely used and has a high frequency of occurrence within the dialect area. It is characterized by its rich semantic meanings and diverse parts of speech, making it one of the most representative common words in Sichuan dialect. However, existing dialect dictionaries have issues such as incomplete definitions, unclear interpretations, and uncertain grammatical properties, which call for further careful revisions. Cognitive linguistics, one of the current research hotspots in linguistics, can fundamentally explain the intrinsic mechanisms and external manifestations of lexical semantic formation. This paper, based on the cognitive perspective and within the macro-framework of Prototype Category Theory, employs the theories of metaphor, metonymy, and image schema to conduct a micro-level analysis and clarification of the original meaning and extended meanings of the Sichuan dialect word ba. It attempts to provide cognitive reasoning for interpreting the meanings of dialect words in dictionaries, as well as to offer new perspectives and cases for exploring the semantics of dialect words.

Some Missionary-Influenced Early Borrowed Words and Names in Xhosa

The contemporary proliferation of borrowed words in Xhosa must be seen as part of a historical process of borrowing, each stage in the process representing a particular orthographic development and contact situation. Research indicates that a large proportion of words that entered the Xhosa lexicon in the nineteenth and early twentieth centuries did so because of missionary influence in the fields of Western commodities and conventions, institutionalised Christianity, the translation of the Bible, the creation of a standard orthography, and mission education. In addition to referencing borrowed words in an early Xhosa dictionary, we illustrate their use for clothes with two advertisements appearing in Xhosa newspapers in the mid-nineteenth century and follow this with a discussion on mission-inspired words and biblical names in a classic 1914 Xhosa novel.

ON THE LEXICAL COMPOSITION OF KAZAKH WORDS FROM THE DICTIONARY OF V.V. RADLOV

The article is devoted to the study of the lexical composition of Kazakh words in V.V. Radlov's dictionary "The experience of the dictionary of Turkic dialects". The most optimal way to achieve this goal is to analyze words by thematic groups. The main feature of this method of research is that only in this way is a high-quality and scientifically complete study of the structure and composition of the Kazakh vocabulary in the general Turkic dictionary achieved. Considering the vocabulary of the Kazakh language of the XIX century by preliminary distribution into thematic groups and further analysis of the composition of these words, it is possible to reveal the full picture of the life of the people during the historical period. The article uses scientific methods of decomposition and systematization by semantic groups, synchronous and diachronic analysis, methods of comparative and comparative analysis. During the thematic analysis of words, it becomes possible to determine the level of linguistic competence of the author, the compiler of the dictionary. This article can serve as an example of the study of the vocabulary of the Kazakh language from a historical-lexicological and historical-lexicographic point of view. As a result, by conducting a thematic analysis of Kazakh words in Radlov's dictionary, it becomes possible to determine the structure and composition of the historical vocabulary of the Kazakh language of the XIX century.

A need analysis of the high-frequency words (HFW) dictionary for the Indonesian language for foreigners (ILF)-1 learning

This is a preliminary study of research development for creating a dictionary of high-frequency words (HFW). Thus, this study tries to analyze the need of the ILF learners as the users of a dictionary of HFW for their ILF learning. A list of high-frequency words should be used in ILF learning so that the learning objectives can be achieved effectively. Unfortunately, the word list is not yet available. The ILF learners, especially those at the beginner level, still have difficulty using the Great Dictionary of the Indonesian Language (KBBI). They prefer using translation apps to obtain the meaning of a word, even though these apps do not always help. Employing a descriptive survey, this study involved a total of 183 ILF teachers and learners. The data were gathered through Google-form questionnaires. In addition, interviews were administered with selected ILF teachers who had a teaching experience of more than 15 years. The findings revealed that the teachers and learners had different beliefs on the vocabulary forms needed for making a dictionary of HFW. The learners still did not understand the concepts of high-frequency words. According to the teachers, HFW was more needed for ILF learning. Meanwhile, for the learners, general words were more needed. Besides, digital dictionaries were more in demand than printed dictionaries. Bilingual dictionaries were more needed than monolingual dictionaries. Both the teachers and learners believed that the dictionary of HFW should comprise sentence examples. They both agreed that the dictionary of HFW should provide information about the use of words in sentence examples, affixes, synonymous phrases, antonyms, word classes, and phonetics. Therefore, the results of this research analysis can be used as a basis for developing a dictionary that fits the needs of ILF-1 learners.

Applied Machine Learning Predictive Analytics to SQL Injection Attack Detection and Prevention

Abstract: The back-end database is pivotal to the storage of the massive size of big data Internet exchanges stemming from cloud-hosted web applications to Internet of Things (IoT) smart devices. Structured Query Language (SQL) Injection Attack (SQLIA) remains an intruder’s exploit of choice on vulnerable web applications to pilfer confidential data from the database with potentially damaging consequences. The existing solutions of mostly signature approaches were all before the recent challenges of big data mining and at such lacks the functionality and ability to cope with new signatures concealed in web requests. An alternative Machine Learning (ML) predictive analytics provides a functional and scalable mining to big data in detection and prevention of SQLIA. Unfortunately, lack of availability of readymade robust corpus or data set with patterns and historical data items to train a classifier are issues well known in SQLIA research. In this project, we explore the generation of data set containing extraction from known attack patterns including SQL tokens and symbols present at injection points. Also, as a test case, we build a web application that expects dictionary word list as vector variables to demonstrate massive quantities of learning data. The data set is pre-processed, labelled and feature hashing for supervised learning. The trained classifier to be deployed as a web service that is consumed in a custom dot NET application implementing a web proxy Application Programming Interface (API) to intercept and accurately predict SQLIA in web requests thereby preventing malicious web requests from reaching the protected back-end database. This project demonstrates a full proof of concept implementation of an ML predictive analytics and deployment of resultant web service that accurately predicts and prevents SQLIA with empirical evaluations presented in Confusion Matrix (CM) and Receiver Operating Curve (ROC).

SWEAR WORDS IN KPOPMINTON TREND AMONG BADMINTON LOVERS IN TWITTER: A STUDY ON LANGUAGE AND GENDER

The phenomenon of the Kpopminton trend among badminton lovers on Twitter lately is very fascinating to discuss. This phenomenon has drawn a lot of criticism from badminton lovers because it combines the worlds of different things, namely K-pop and badminton. The aim of this research is to investigate the forms and references of swearing, as well as differences in gender forms of swearing in Kpopminton trends that occur on Twitter among badminton fans. This research uses a descriptive approach with qualitative methods. Data collection was carried out using the notetaking and listening method. The results of this research show that comments on the Kpopminton trend among badminton fans on Twitter contain a lexicon of swear words, where the male gender is wider and more varied. Swearing is classified based on its morphological and syntactic lingual form, as well as its linguistic form. Referents of swear words used by men are conditions, animals, activities, objects, and body parts. Meanwhile, women use more polite referents, although they still tend to be rude, namely referents related to objects and animals. Lastly, men tend to use more swear words than women with a harsher choice of curse words as can be seen from the level. The level of swear words shows that in terms of extreme levels the curses are spoken by men. At high levels, it is spoken by both men and women. Meanwhile, at the standard level it is spoken by women.