Evolution Of Vocabulary Research Articles

Digital Evolution: Exploring the Impact of Social Media on Local Dialects and Lexicon; An Examination of Central Kurdish Language

This study suggests a digital linguistic approach to multi-mediated communication (MMC), drawing on a case study of language variation on social media. In the early 21st century, social media (SM) has significantly impacted various aspects of human life, including language, as articulated within the theoretical framework of digital linguistics and language variation. This study explores the influence of SM on Kurdish local dialects in Iraqi Kurdistan, with a focus on vocabulary evolution and the ongoing challenge of dialect standardization. Given the high unemployment rates in Iraq, which have led to increased SM engagement, this research examines how these platforms affect dialect usage across diverse demographic groups. Utilizing a mixed-methods approach, the study integrates qualitative content analysis and quantitative surveys to assess SM's role in shaping linguistic practices. Findings reveal thatolder generations are more likely to maintain traditional dialects, while younger users increasingly adopt standardized Kurdish forms. The study highlights SM's dual impact: promoting linguistic convergence while posing risks to dialectal diversity. It emphasizes the need for a balanced approach that supports regional dialects alongside the benefits of standardization, advocating for strategic initiatives to preserve linguistic heritage while adapting to digital influences.

Likelihood calculation in a multistate model of vocabulary evolution for linguistic dating

Abstract Computational methods of language dating make inferences about the divergence times of protolanguages by evaluating the patterns of inheritance in the vocabulary of modern languages, given the specification of a model of vocabulary evolution. We consider a model that describes vocabulary evolution as the replacement of traits by new traits from an infinite state space along a tree. This model has been introduced in previous literature but so far it has not been used in many applications. We give a general recursive algorithm for calculating likelihoods and argue that the model gives a more realistic representation of vocabulary evolution over time, compared to existing models like the Stochastic Dollo model. We also provide a case study demonstrating the model’s potential applications.

Features of a FAIR vocabulary

BackgroundThe Findable, Accessible, Interoperable and Reusable(FAIR) Principles explicitly require the use of FAIR vocabularies, but what precisely constitutes a FAIR vocabulary remains unclear. Being able to define FAIR vocabularies, identify features of FAIR vocabularies, and provide assessment approaches against the features can guide the development of vocabularies.ResultsWe differentiate data, data resources and vocabularies used for FAIR, examine the application of the FAIR Principles to vocabularies, align their requirements with the Open Biomedical Ontologies principles, and propose FAIR Vocabulary Features. We also design assessment approaches for FAIR vocabularies by mapping the FVFs with existing FAIR assessment indicators. Finally, we demonstrate how they can be used for evaluating and improving vocabularies using exemplary biomedical vocabularies.ConclusionsOur work proposes features of FAIR vocabularies and corresponding indicators for assessing the FAIR levels of different types of vocabularies, identifies use cases for vocabulary engineers, and guides the evolution of vocabularies.

DEEP, a methodology for entity extraction using organizational patterns: Application to job offers

Plain texts written in natural language may have several specific features, such as organizational patterns and an ambiguous and evolving vocabulary. From the literature, entity extraction approaches are not sufficient to consider these specific features jointly. To address this issue, we propose DEEP, a methodology that improves the quality of entity extraction by using organizational patterns through a sequence labelling technique. To this end, DEEP creates a high-quality corpus and relies on an appropriate learning algorithm. DEEP is validated on a real corpus of job offers. Experiments show that (1) considering organizational patterns improves the quality of entity extraction, (2) vocabulary evolution is taken into consideration and ambiguity in vocabulary is reduced, (3) DEEP provides clear guidelines for the creation of a high-quality corpus for entity extraction, (4) the Bidirectional Long Short-Term Memory + Conditional Random Field architecture for sequence labelling is the one that takes the most advantage of the organizational patterns.

Main trends in the economic vocabulary evolution of the modern Ukrainian language (based on famous Ukrainian linguists scholarly works of the early XXI century)

Research rationale. In the modern world globalization processes affect the development of every sphere of Ukrainian society, including international politics, technical and military sector, education, science, sports, and of course economics. Due to various globalization processes, on one hand and nationalization processes on the other, Ukrainian vocabulary is actively extended with new words through various thematic groups as an open language system. The economic theme group of Ukrainian vocabulary has become especially rich over the last three decades. This fact of course constantly attracts the attention of modern linguists. Problem statement. More and more citizens of our country are involved in a variety of economic processes lately. This leads not only to the active acquisition of special and common economic terms by citizens, but also their modeling and reinterpretation. Along with vocabulary which is well-known only to a small circle of economists, commonly used economic lexis is actively formed. Such processes which are constantly studied by Ukrainian modern linguists always demand reenvisioning in the context of the integral development of Ukrainian vocabulary. Analysis of recent researches and publications. Dynamic lexis processes of the modern Ukrainian language have been actively studied by such well-known modern linguists as K. Horodenska, S. Yarmolenko, L. Lysychenko, O. Serbenska, and L. Struganets. Economic vocabulary of the modern language of the early XXIst century is the researches study object of such linguists as N. Klymenko, O. Styshov, M. Navalna, E. Karpilovskaya, L. Kislyuk. The purpose of the article is to analyze modern Ukrainian linguist’s researches and to find out leading trends in economic lexis of Ukrainian language at this level of development. Research methodology. The following methods of scientific research are used in the article: comparative analysis, benchmarking assessment, systematic approach, and synthesis. Work results. Ukrainian language principal trends of modern economic vocabulary have been analyzed in the article inspired by the works of famous Ukrainian linguists of the early XXIst century. Also there have been researched ways to enrich thematic economic group of the vocabulary. Conclusions. It is detected that the economic thematic group of Ukrainian lexis develops according to the following tendencies in the works of famous Ukrainian linguists: 1) globalization and autochthonization; 2) active assimilation by speakers of economic words with both direct and figurative meaning; 3) transfusion of special word-terms and commonly used lexical units in various spheres of communication, as in professional so in journalistic and colloquial.

2010년-2016년의 중국 신조어 생성 현황 분석

This paper analyzed how Chinese nelogism were generate from 2010 to 2016. And from 2010 to 2016 of in the nelogism, we extracted a group of nelogism and examined the semantic and morphological aspects of the nelogism. First, the annual production of nelogism, composition of syllables, composition of nelogism, and unusual forms of nelogism were examined, and the analysis was conducted by extracting the same type of nelogism. The analysis materials is 侯敏, 邹煜, 周荐, 杨尔弘writed 『2010 汉语新词 语』, 『2011 汉语新词语』, 『2012 汉语新词语』, 『2013 汉语新词语』, 『2014 汉语新词语』, 『2015 汉语新词语』, 『2016 汉语新词语』. This study can help in the evolution of vocabulary in Chinese, vocabulary education, and research on Chinese society and people's consciousness, and I would like to conduct more specific research on the Chinese neologism group in the future based on the discussion of the main body.

Likelihood category game model for knowledge consensus

To reach consensus among interacting agents is a problem of interest for social, economical, and political systems. To investigate consensus dynamics, naming game, as a computational and mathematical framework, is commonly used. Existing works mainly focus on the consensus process of vocabulary evolution in a population of agents. However, in real-world cases, naming is not an independent process but relies on perception and categorization. In order to name an object, agents must first distinguish the object according to its features. We thus articulate a likelihood category game model (LCGM) to integrate feature learning and the naming process. In the LCGM, self-organized agents can define category based on acquired knowledge through learning and use likelihood estimation to distinguish objects. The information communicated among the agents is no longer simply in some form of absolute answer, but involves one’s self perception and determination. With its distinguished features, LCGM allows coexistence of multiple categories for an observation. It also provides quantitative explanation that consensus is hard to be reached among serious agents who have a more complex knowledge formation. The proposed LCGM and this study are able to provide new insights into the emergence and evolution of consensus in complex systems.

Устаревшая лексика русского языка: вопросы преподавания и лексикографической интерпретации

The research is devoted to lexicographic and educational issues associated with obsolescent words in the Russian language. Unresolved theoretical issues, i. e. a classification of obsolete vocabulary, research on obsolete words in connection with the chronology of their use in the language, etc., complicates applied research, teaching and lexicographical description of such vocabulary. Within the educational process it is important not only to interpret the meaning of obsolete lexical units found in classical literature, but also to enable students to understand the systematic nature, the dynamism, and the historical character of the vocabulary evolution phenomenon. It is necessary to consider the different degree of obsolescence and the processes of vocabulary update typical for the development of the modern Russian language. The author suggests that dictionaries should also be used in the process, i. e., dictionaries of rare and obsolete words, explanatory dictionaries, and, additionally, historical dictionaries. The features of the lexicographic presentation of obsolete vocabulary should also be taken into consideration. The central issues of explanatory lexicography in this regard are the following: criteria for including obsolete lexis in dictionaries, and principles of its description (a system of lexicographic notes and typical explanations, various interpretations of historicisms and archaisms, etc.). The article discusses the lexicographic practice of academic dictionaries (in particular, the “Dictionary of the Modern Russian Language”) and the innovative project titled “The Dictionary of the Russian Language of the 21st Century”, supervised by G. N. Sklyarevskaya. The author suggests that an essential advantage of the explanatory dictionary is that it can define the role and features of outdated vocabulary functioning in the modern language, interpreting this vocabulary as an integral part of the lexical composition of the Russian language. The author concludes that studying obsolete vocabulary at school and making its descriptions available for users in modern Russian language dictionaries are important prerequisites for correct interpretation and use of obsolete words and expressions.

Domain learning naming game for color categorization.

Naming game simulates the evolution of vocabulary in a population of agents. Through pairwise interactions in the games, agents acquire a set of vocabulary in their memory for object naming. The existing model confines to a one-to-one mapping between a name and an object. Focus is usually put onto name consensus in the population rather than knowledge learning in agents, and hence simple learning model is usually adopted. However, the cognition system of human being is much more complex and knowledge is usually presented in a complicated form. Therefore, in this work, we extend the agent learning model and design a new game to incorporate domain learning, which is essential for more complicated form of knowledge. In particular, we demonstrate the evolution of color categorization and naming in a population of agents. We incorporate the human perceptive model into the agents and introduce two new concepts, namely subjective perception and subliminal stimulation, in domain learning. Simulation results show that, even without any supervision or pre-requisition, a consensus of a color naming system can be reached in a population solely via the interactions. Our work confirms the importance of society interactions in color categorization, which is a long debate topic in human cognition. Moreover, our work also demonstrates the possibility of cognitive system development in autonomous intelligent agents.

Evolution of Vocabulary in the Poetry of Sylvia Plath

In this study, we provide a quantitative analysis of the temporal evolution of word choice across the career of Sylvia Plath, a poet who suffered from mental illness, which culminated in her suicide. Her work provides an excellent case study for temporally indexed changes in vocabulary due to well-dated records of her productivity. We use simple functions to discriminate bulk trends in her vocabulary and classify words into those that accelerate, decelerate, or represent consistency in usage. Overall, we find that Plath’s vocabulary was exceptionally consistent throughout her career from 1956 to 1963; however, we observe relative changes in the frequency of words used. Two examples of this evolution are in her use of colours and personal pronouns. Namely, we note a consistently increasing preference towards black and white above other colour words from 1956 to 1963 and, in contrast, we observe a marked transition from dominant use of third-person feminine to dominant use of first-person singular in her later work. We find that the most dynamic changes in word use occurred between March and May 1959 and we tie these observations to events recorded in Plath’s journal entries. We propose that our function-discrimination approach offers a vital tool in the objective analysis of word-use for understanding style evolution and for correlation with a poet’s life events that may influence their work.

Studying tag vocabulary evolution of social tagging systems in learning object repositories

In the field of Technology-enhanced Learning (TeL), social tagging has been applied to Learning Object Repositories (LORs) mainly as a means:(a) to offer an alternative way of classifying the Learning Objects (LOs) based on the tag vocabulary created by the end-users of the LOs, and (b) to facilitate the enhancement of LOs’ descriptions via collaborative tagging. However, in order to be able to understand how a social tagging system performs and whether it can deliver the aforementioned goals, it is important to be able to investigate the evolution of the tag vocabulary, which constitutes the core component of a social tagging system. Within this context, research has focused on different facets of social tagging systems such as the growth of the tag vocabulary, the frequency and reuse of tags, as well as the stability of the tag vocabulary but there are only sporadic studies for investigating these issues in the field of LORs. This paper aims to contribute in studying how social tagging systems perform in the context of LORs by investigating the evolution of the tag vocabulary in OpenScienceResources Repository, a science education domain specific repository with a rich dataset operating in Europe for 5 years.

Kâroly Gadânyi, The Evolution of Vocabulary in literary Slovenian, Melbourne Academia Press, Melbourne 1996

Kâroly Gadânyi, avtor angleško pisane knjige o razvoju slovenskega knjižnega besedja, je jezikoslovec slavist, ki se med drugim intenzivno študijsko ukvarja tudi s slovenistiko.

From the <em>regimen sanitatis</em> to literature. Arnau de Vilanova’s case

Analysis of the evolution of vocabulary in the two manuscripts that have preserved the Catalan translation carried out by Berenguer Sarriera of Regimen sanitatis ad regem Aragonum by Arnau de Vilanova. The comparison of the vocabulary of the two manuscripts, copied a century apart, demonstrates the effort of both copysts to adapt to contemporary uses. The adaptation of the scripta to temporary uses of every copyst indicates the usefulness of the genre of regimina sanitatis and the existence of a public willing to acquire this type of works, especially if they are translated into the vernacular language. Another indicator of the success and diffusion of this medical genre is the presence of its own concepts and terminology in literary works. This paper presents some examples from the Llibre de meravelles by Ramon Llull, Lo Crestia by Francesc Eiximenis, Curial e Guelfa, Tirant lo Blanc by Joanot Martorell and l’Espill by Jaume Roig.

The Evolution of Vocabularies and Its Relation to Investigation of White-Collar Crimes: An Institutional Work Perspective

White-collar crimes are illegal and unethical actions by agents of an organization. In this paper, we address two related research questions concerning white-collar crime—how did the language of white-collar crime evolve? And how did this language co-evolve with the investigation of white-collar crime? Building on research on institutional work, we find that key institutional actors such as the Presidential Office are likely to use frames and adopt a particular language (i.e., the term “white-collar crime”) in order to legitimize institutional practices (i.e., investigation of white-collar crimes). Conversely, less powerful actors such as the law enforcement agencies are then likely to use narratives to shape language in order to mobilize other stakeholders to continue the adoption of the referent practice. We uncover these findings by using qualitative methodology and trend analysis. We conclude with a detailed theoretical discussion of the role of institutional actors in institutional work and the implications of our research.

The role of sound symbolism in protolanguage: Some linguistic and archaeological speculations

In this paper, I have tried to clarify the role of sound symbolism in the early development of human language vocabulary The mimicking of natural sounds by means of an articulated language, producing onomatopoeic sound-symbolism could be considered as one first stage in human language vocabulary evolution. The following step consists in using sounds to symbolize phenomena perceptible by non-auditory senses. Sound symbolization began to relate certain sounds to the visual aspects of objects such as size or shape or to certain aspects of actions and states. This is called pheno-mimic sound-symbolism. The transition from phono-mimic or onomatopoeic sound symbolism to pheno-mimic sound representations can be related to the stage of human mind evolution proposed by S. Mithen (1996) in which domain-specific modules work together with a seamless flow of information across different domains. This is called cognitive fluidity. This cognitive fluidity could be responsible for the connection between different cognitive abilities: visual processing, auditory processing and the socialsemiotic activity of linguistic symbolism.

Random Drift versus Selection in Academic Vocabulary: An Evolutionary Analysis of Published Keywords

The evolution of vocabulary in academic publishing is characterized via keyword frequencies recorded in the ISI Web of Science citations database. In four distinct case-studies, evolutionary analysis of keyword frequency change through time is compared to a model of random copying used as the null hypothesis, such that selection may be identified against it. The case studies from the physical sciences indicate greater selection in keyword choice than in the social sciences. Similar evolutionary analyses can be applied to a wide range of phenomena; wherever the popularity of multiple items through time has been recorded, as with web searches, or sales of popular music and books, for example.

Evolution of vocabulary on scale-free and random networks

We examine the evolution of the vocabulary of a group of individuals (linguistic agents) on a scale-free network, using Monte Carlo simulations and assumptions from evolutionary game theory. It is known that when the agents are arranged in a two-dimensional lattice structure and interact by diffusion and encounter, then their final vocabulary size is the maximum possible. Knowing all available words is essential in order to increase the probability to “survive” by effective reproduction. On scale-free networks we find a different result. It is not necessary to learn the entire vocabulary available. Survival chances are increased by using the vocabulary of the “hubs” (nodes with high degree). The existence of the “hubs” in a scale-free network is the source of an additional important fitness generating mechanism.

Cultural adaptation and institutional change: The evolution of vocabularies of corporate governance, 1972–2003

Drawing on content analysis, text interpretation, and historical analysis, we develop a grounded theory to explain the evolution of vocabularies of corporate governance. The term corporate governance emerged in the 1970s as frame to explain contemporary corporate scandals. While the word has increased in usage and became institutionalized, its meaning has evolved, as other words that co-occur in the vocabulary have shifted both in response to subsequent environmental events and to framing processes. We propose an evolutionary theory of cultural adaptation as meanings evolve through (1) path-dependent conceptual blending (variation); (2) differential adoption shaped by the cultural resonance of words (selection); and (3) increased persistence due to institutionalized theorization (retention). Our evolutionary theory of cultural adaptation posits a recursive relationship between culture and the economy, where cultures adapt to economic change, and the “stickiness” of culture and path dependence results in its relative autonomy as an explanatory force in economic change.

The evolutionary language game: An orthogonal approach

Evolutionary game dynamics have been proposed as a mathematical framework for the cultural evolution of language and more specifically the evolution of vocabulary. This article discusses a model that is mutually exclusive in its underlying principals with some previously suggested models. The model describes how individuals in a population culturally acquire a vocabulary by actively participating in the acquisition process instead of passively observing and communicate through peer-to-peer interactions instead of vertical parent–offspring relations. Concretely, a notion of social/cultural learning called the naming game is first abstracted using learning theory. This abstraction defines the required cultural transmission mechanism for an evolutionary process. Second, the derived transmission system is expressed in terms of the well-known selection–mutation model defined in the context of evolutionary dynamics. In this way, the analogy between social learning and evolution at the level of meaning–word associations is made explicit. Although only horizontal and oblique transmission structures will be considered, extensions to vertical structures over different genetic generations can easily be incorporated. We provide a number of simplified experiments to clarify our reasoning.

Adaptable architecture generation for embedded systems

Architecture generation is the first step in the design of software systems. Many of the qualities that the final software system possesses are usually decided at the architecture development stage itself. Thus, if the final system should be usable, testable, secure, high performance, mobile and adaptable, then these qualities or non-functional requirements (NFRs) should be engineered into the architecture itself. In particular, recently adaptability is emerging as an important attribute required by almost all software systems. Briefly, adaptability is the ability of a software system to accommodate changes in its environment. Embedded systems are usually constrained both in hardware and software. Current adaptable architecture development methods for embedded systems are usually manual and ad hoc––there are almost no comprehensive systematic approaches to consider NFRs at the architecture development stage. While there are several examples of approaches to generate architectures based on functional requirements, we believe that there are very few techniques that consider NFRs such as adaptability during the process of architecture generation. In this paper we present an automated design method that helps develop adaptable architectures for embedded systems by developing a tool called Software Architecture Adaptability Assistant (SA3). SA3 helps the developer during the process of software architecture development by selecting the architectural constituents such as components, connections, patterns, constraints, styles, and rationales that best fit the adaptability requirements for the architecture. The developer can then complete the architecture from the constituents chosen by the tool. SA3 uses the knowledge base properties of the NFR Framework in order to help automatically generate the architectural constituents. The NFR Framework provides a systematic method to consider NFRs, in particular their synergies and conflicts. We validated the architectures generated by SA3 in a type of embedded system called the vocabulary evolution system (VES) by implementing the codes from the generated architectures in the VES and confirming that the resulting system satisfied the requirements for adaptability. A VES responds to external commands through an interface such as ethernet and the vocabulary of these commands changes with time. The validation process also led to the discovery of some of the shortcomings of our automated design method.