Semantic Analysis Research Articles

Exploring Word-Level Representations in Modern Natural Language Processing

Abstract: Natural Language Processing (NLP) is a dynamic and rapidly advancing field at the intersection of artificial intelligence and linguistics, focused on enabling computers to understand, process, and generate human language. Recent advancements intransformer-based models have significantly improved NLP capabilities, enablingmachines to understand and generate human language more effectively. This paper provides a comprehensive overview of NLP, tracing its historical development and recent trends. The discussion includes the different phases of NLP, from text pre- processing and tokenization to syntactic and semantic analysis, along with pragmatic considerations. Text normalization techniques, such as stemming, lemmatization, and removing stopwords, are explored to emphasize their importance in preparing raw text for analysis. Additionally, this paper presents a comparative analysis of popular word-level representation techniques used in NLP, including One-Hot Encoding, Bag of Words (BoW), and Term Frequency-Inverse Document Frequency (TF-IDF).

Automatic Negation Detection for Semantic Analysis in Arabic Hotel Reviews Through Lexical and Structural Features: A Supervised Classification

One significant challenge in sentiment analysis is the presence of negation, which reverses the meanings of sentences, transformingpositive statements into negative ones and impacting the sentiment conveyed in the text. This issue is particularly pronounced in Arabic, a language known for its complex morphology. Detecting negation is crucial for enhancing sentiment analysis performance and various natural language processing applications. This paper presents an approach for automatically detecting negation in user-generated Arabic hotel reviews through lexical and structural features. It comprises several stages: data collection, text pre-processing, feature extraction, supervised learning classification, and evaluation. The study employed multiple supervised classification techniques, including naïve Bayes, random forest, logistic regression, support vector machines, and deep learning, to analyse lexical and structural features extracted from the dataset. The results of the experiments yielded promising outcomes, demonstrating the feasibility of the approach for practical applications. The classifiers exhibited highly comparable performance in identifying negation, with only marginal deviations in their performance metrics. Notably, the deep learning classifier consistently emerged as the top performer, achieving an exceptionally high overall accuracy rate of 99.24 percent, surpassing established benchmarks in Arabic text processing and underscoring its potential for practical applications. These findings hold significant implications for advancing Arabic text processing, particularly in sentiment analysis and related NLP tasks. The high accuracy of 99.24 percent achieved by the deep learning classifier highlights its robustness in accurately detecting negation, a critical challenge in sentiment analysis. This classifier performance demonstrates the potential to be integrated into real-world applications, such as automated review systems and opinion mining tools, where accurate sentiment interpretation is essential.

Logical Spaces and Subjunctive Tenses

Apparently, Subjunctive tenses express temporal location, and, in some constructions, the past subjunctive can also express modal values. A long-standing debate exists over whether—even in the latter case—verbal tenses are temporal operators or whether in some constructions they convey temporal meaning, and in others they have a modal value, maybe derived from their basic temporal meaning. The assumption that the basic meaning of subjunctive tenses are of a temporal nature is challenged by the fact that the future subjunctive, which exists in Portuguese, has the same temporal interpretation as the present subjunctive, with which it is in complementary distribution. Moreover, no clear modal difference is observed between the future and present subjunctive tenses. In this paper, I present arguments against the separation of the temporal and modal values of the subjunctive tenses. I posit, instead, that a semantic analysis of subjunctive morphemes must consider ordered pairs of times and possible worlds; only in this way can we adequately capture the observed data and allow a comprehensive view of the system of subjunctive tenses in Portuguese (which will be extendable to Romance languages in general). If we accept this proposal, then the modal as temporal information associated with subjunctive tenses follows naturally, including the systematic futurate reading of subjunctive temporal clauses.

The ninth art, tells the story of cultural China and the world: Cultural interaction in cross-cultural video game communication-based on 'Genshin Impact' YouTube comments.

China has attached increasing importance to the overseas dissemination of traditional culture as it continues to strengthen its comprehensive national strength and develop globalization initiatives. The electronic game, as the 'ninth art', with its booming development and inherent cross-cultural communication platform attributes, has taken on the important task of taking culture abroad. This study selects 'Genshin Impact', a game highly praised and well-received globally, which contains an abundance of Chinese cultural elements and cultural elements from various regions of the world, to study cultural interaction in cross-cultural communication of electronic games. This study conducts text sentiment analysis and semantic network analysis on the comments of 'Genshin Impact' videos on the overseas video platform YouTube and studies the cultural interaction in the cross-cultural communication of the 'ninth art', telling the cultural stories of China and the world from a multicultural perspective. The study found that games and derivative videos triggered positive emotional responses from audiences both at home and abroad. While experiencing pleasure and surprise, audiences also arouse deeper emotions such as admiration, identification, and expectation. Meanwhile, in the complex art form of the 'ninth art', audiences can absorb the cultural elements of different cultures, resonate with the elements of their cultural circle, and even trigger further profound thinking. Finally, this study provides constructive suggestions on using the 'ninth art' to better 'tell China's stories and disseminate China's voice'.

Проект Стратегии противодействия экстремизму в Российской Федерации – политический анализ новых подходов в спектре современных угроз

The article delves into the analysis of the document titled “Strategy for Counteracting Extremism in the Russian Federation”, proposed for adoption by the Ministry of Internal Affairs of Russia, with a focus on its alignment with current challenges and threats in the sphere of national security. The author concludes that the project successfully develops and complements the provisions of the existing Strategy for Counteracting Extremism in the Russian Federation until 2025, incorporating new threats arising from the exacerbated geopolitical situation. These threats include the intensified activities of foreign intelligence and sabotage services aimed at recruiting underage Russian citizens, the introduction of non-traditional forms of Islam unfamiliar to the indigenous peoples of Russia and their subsequent radicalization, and the covert use of sports organizations for the preparation of extremists. However, the author observes that certain provisions and formulations within the project require clarification. Specific terms such as xenophobia, Russophobia, and the correlation between extremist and terrorist activities need to be defined with greater precision. The author also highlights potential issues that may arise from the use of quantitative indicators for measuring the success of the Strategy’s implementation. In conducting this research, the author employed various methods including a systematic approach, multifactor analysis, the principle of historicism, and logical and semantic analysis of documents. These methodological frameworks facilitated a comprehensive examination of the proposed strategy in light of modern challenges and the evolving landscape of threats to national security.

Социальные сети как современный тотальный институт

The modern Internet space, especially in the context of social networks, can be viewed through the prism of the theory of total institutions. This article delineates the concept of a total institution, outlining the genesis of its constituent categories. Drawing upon the ideas of E. Goffman, M. Foucault, and P. Bourdieu, a characterization of the total institution is presented. The scientific reflection on this topic within the domestic academic community is also reviewed. Employing semantic analysis and critical discourse analysis methods, the article identifies two potential approaches to applying the category of “total institution” for the analysis of communication in the internet space: first, the social network reproduces similar structures within itself, isolating certain subjects while endowing others with preferences, thereby functioning analogously to social and political systems; second, the social network itself is a total institution, set in opposition to the ordinary world. Conclusion emphasizes the functionality of four parameters through which a social network can be conceptualized as a total institution: enclosed space, rhythmic time, control, and disciplinary practices. These characteristics amplify their impact on the speaking subject under the conditions of the dominance of a quasi-political discourse, prevalent in social networks.

An Efficient Archerfish Hunting Optimizer (AHO)-Based Power Quality Improvement in Distribution System Connected UPQC

These days, because power quality (PQ) issues are costing industrial customers a lot of money, both electrical utilities and end-users are paying a lot of attention to them. The most significant and frequent PQ concerns for sensitive loads are voltage sag and swell. This manuscript proposes an optimization technique for enhancing the control system of a unified power quality conditioner (UPQC) connected solar photovoltaic system in the distributed generation system. The proposed strategy is the archerfish hunting optimizer (AHO). The objective of the AHO approach is to optimizing UPQC operation in distribution systems, focusing on targeted power quality enhancement. The optimal control pulses are produced by the series active power filter and the shunt active power filter, depending on the load-side and source circumstances. During the load variation states the AHO technique manages the power loss, total harmonic distortion (THD), and voltage instability issue respectively. The performance of the AHO methodology is carried out on the MATLAB platform and compared with existing methods, like particle swarm optimization (PSO), latent semantic analysis (LSA), and ant-lion optimizer (ALO). The existing methods THD are 6.35%, 7.85%, and 9.19%. The proposed method of THD is 4.22%. From the outcome, it concluded that the proposed method based on the THD is low contracted to present techniques.

Life values in Russia and China: Semantic analysis and comparison

The paper seeks to explore the core life values of people living in Russia and China using an online survey in the respondents’ native languages with samples of 887 and 559 participants from each country respectively, who were asked to think of three words associated ‘with something most important in life’. The word-association arrays were translated into English by an automatic translator; then we compared the frequencies of individual words or those of their meanings obtained using the Roget’s Thesaurus. The words ‘family’ and ‘love’ were the most frequent in both samples, but the frequencies of these and most of the other words from the semantic core of each sample differed significantly. Analyses at the level of semantic vectors showed that more than half of the meanings that Russian respondents described as important and more than a third of the meanings important to the Chinese respondents had significant differences in frequencies between the samples. The paper presents 62 semantic groups of the Roget’s Thesaurus, the frequencies of which are reliably different; these are the meanings in which the Chinese and Russian samples differ with regard to life values. There are also 26 semantic groups, the frequencies of which are statistically the same and comparatively high in both samples: these are the common meanings. The results may be used in the design of automatic and AI systems to reduce the intercultural barriers.

Historical analogies, traumatic past and responses to the war in Ukraine

Abstract This article examines the use of historical analogies by political leaders during foreign policy crises. Specifically, we focus on the German, Polish and Czech leaderships' reactions to Russia's invasion of Ukraine and investigate the historical analogies which leaders invoked to justify their responses to Russia's aggression. The existing scholarship recognizes the importance of historical analogies in foreign policy decision-making, but the literature focuses predominantly on several high-profile analogies (i.e. the Munich Agreement or the Vietnam War) and lacks comparative perspective. We employ a dual-method approach that combines qualitative coding with semantic network analysis, and conduct a comparative analysis of the full spectrum of analogies used by Polish, Czech and German policy-makers. We find that politicians did not focus on a single overarching analogy, but employed a wide array of historical references. We also find that even though the countries' policies largely aligned and that their leaders often invoked the same events, the meaning of analogies and the signals they sent differed substantially across cases. Analysing the full spectrum of analogies demonstrates that justifications for supporting Ukraine were shaped more by these states' own historical traumas than by their sympathy for Ukraine, support for international law, or desire to uphold the rules-based international order.

Representations of Trust and Distrust in Financial Institutions in Russian Regional Speech Culture

The article is devoted to a comparative analysis of the representation of trust and distrust in financial institutions in the language and speech culture of the Russian province. The use of the constructivist methodology of P. Bourdieu made it possible to interpret trust as an internal component of the practices of an agent involved in the current situation in the financial market. The content analysis of 55 semi-structured interviews with three generations of residents of the region showed that the conservative model of financial behavior continues to be reproduced in the speech culture. The difference between generations is less noticeable against the background of a significant difference between residents of rural and urban settlements. The study revealed a high level of resentment associated with the collective memory of the collapse of the USSR and privatization. All generations in rural settlements showed a low level of assessment of their own financial situation, while both rural and urban informants had a rather pessimistic representation of social change. Semantic analysis revealed the dominance of the image of the state as a “collector of payments” in their consciousness, and to a lesser extent, an “assistant” supporting a person in their relationship with financial institutions.

C-Agree is local subject-verb agreement in Kipsigis

AbstractUpwards-oriented complementizer agreement raises questions about the directionality and locality of agreement. Based on novel data from original fieldwork, we argue that what has been described as an agreeing ‘say’-based complementizer in Kipsigis (Diercks and Rao 2019; Diercks et al. 2020) is the lexical verb ‘say,’ and what looks like C-Agree is in fact agreement between this verb and its locally introduced (often covert) subject. Our analysis highlights that ‘say’-based complementizers might be of category V, not C, in more languages than previously thought (Koopman 1984; Major 2021), which means that some instances of what has been described as C-Agree may instantiate standard verbal agreement. Furthermore, we provide a semantic analysis of ‘say’-based complementation in Kipsigis along the lines of contentful eventualities (Hacquard 2006; Kratzer 2013a).

Middle Leadership in Educational Teams: Practices and Effects on the Development of Learning Communities

In a new context of management and teaching action, framed by the organisation of the school into educational teams, middle leaders can play a key role in promoting learning communities, teacher development and improving teaching. Therefore, it seems relevant to understand the practices of these leaders that make their leadership effective. To this end, we adopted a qualitative research paradigm, operationalised through a case study, combining a quantitative and qualitative approach. Thus, we articulated data analysis processes based on descriptive statistics, which we subjected to structural and semantic analysis and interpretation, with a qualitative approach, essentially based on content analysis, to delve into some unique contexts and the perspective of individual actors. After analysing the data, we conclude that educational team coordinators play a fundamental role in facilitating the interpersonal characteristics of learning communities, involving teachers in a more collaborative and collegial working environment. However, their role in facilitating teacher learning is weaker, which hinders their contribution to deepening teacher learning and changing classroom practices.

Blue-cloud DAB: developing a platform to harmonize, assess and disseminate marine metadata collections

AbstractThe integration and harmonization of marine data from diverse sources are vital for advancing global oceanographic research and ensuring seamless discovery and access of critical datasets. This paper presents a comprehensive analysis of the metadata harmonization efforts within the Blue-cloud 2026 project, which brokers data from numerous Blue Data Infrastructures (BDIs), leveraging the Discovery and Access Broker technology. The platform enables discovery and analysis of marine data collections while facilitating interoperability with other components of the marine digital ecosystem, such as virtual laboratories and the Semantic Analyzer. It also supports the flow of Blue-cloud information to other initiatives like the Global Earth Observations System of Systems. For data managers, the findings emphasize the importance of enhancing metadata quality, revealing discrepancies in core metadata elements, and the need for more consistent use of controlled vocabularies. For cyberinfrastructure developers, the study details the challenges of accommodating a wide array of interfaces from different data systems, highlighting the adoption of an extensible brokering architecture that harmonizes metadata models and protocols. The study also emphasizes the importance of metadata analysis in ensuring effective searches for end users, highlighting challenges in aggregating diverse sources, where data providers may have structured the content with different objectives compared to those of the system of systems. End users will gain insights into the current metadata content of Blue-cloud, enabling them to search and access data from multiple BDIs with an understanding of the technical complexities behind the scenes.

The Relationship Between Misinformation And Social Noise And Their Impact On The Information Ecosystem

Social noise and social entropy are new concepts modeled after Shannon’s information and communication theory, in which the interference of noise between the sender and receiver is measured using entropy. Social noise in the context of social media plays a vital role in magnifying and spreading misinformation, which in turn impacts the overall information ecosystem. Ecosystems are made of interconnected and integrated parts that rely on one another to maintain balance and survive. Studies related to social noise and misinformation have shown that social noise can contribute significantly to spreading misinformation and potentially alter the original intended message (Alsaid & Pampapura, 2022); Alsaid et al. (2024). paper investigates methods of quantifying social noise using entropy to minimize the spread of misinformation on social media, particularly X. Using a combination of Uncertainty Reduction Theory (URT) and Social Entropy, data analysis was performed using one million tweets harvested from #Ukraine. Data analysis involved several methods: sentiment analyses, term association, network maps, and entropy computation. Results have shown a direct relationship between social noise and social entropy as a measure of uncertainty. Also, social noise and uncertainty decrease with the use of URLs and rich content. It is evident from the results that the entropy value is influenced by the accuracy of keywords identified using topic modeling as descriptive of social noise constructs. Semantic analysis of tweets can help improve the definition of social noise constructs, leading to enhanced and more accurate entropy calculation. Future studies may consider advanced machine learning and AI

Def2Vec: you shall know a word by its definition

AbstractDef2Vec introduces a new perspective on building words embeddings by using dictionary definitions. By leveraging term-document matrices derived from dictionary definitions and employing Latent Semantic Analysis (LSA), our method, Def2Vec, yields embeddings characterized by robust performance and adaptability. Through comprehensive evaluations encompassing token classification, sequence classification and semantic similarity, we show empirically how Def2Vec consistently demonstrates competitiveness with established models like Word2Vec, GloVe, and FastText. Notably, our model’s utilization of all the matrices resulting from LSA factorisation facilitates efficient prediction of embeddings for out-of-vocabulary words, given their definition. By effectively integrating the benefits of dictionary definitions with LSA-based embeddings, Def2Vec builds informative semantic representations, all while minimizing data requirements. In this paper, we run different experiment to assess the quality of our embedding model at word level and at sequence level. Our findings contribute to the ongoing evolution of word embedding methodologies by incorporating structured lexical information and enabling efficient embedding prediction.

Semantic Analysis and Construction of English Discourse Based on Intelligent CAD Tutoring Systems

Semantic Analysis and Construction of English Discourse Based on Intelligent CAD Tutoring Systems

Analysis of policy changes for Yangtze River Basin governance from 1980 to 2022—based on semantic analysis method and punctuated equilibrium theory

The governance policies have a prominent impact on the development and regional planning of the Yangtze River Basin, a key region for China to achieve modernization. Taking the public policy documents issued by China’s central government for the Yangtze River Basin from 1980 to 2022 as the research object, this paper introduces the NLP (Natural Language Processing) technology and semantic analysis methods to carry out quantitative research on policies. This study first examines the textual connotations of the policies and the characteristics of the policy changes based on the LDA (Latent Dirichlet Allocation) model to determine how policy changes occur for the governance of the Yangtze River Basin. Using the punctuated equilibrium theory, it then conducts two case studies in which the implications of specific major events are analyzed in depth. Research has shown that the changes in governance policies for the Yangtze River Basin are characterized by gradual changes and intermittent mutation, roughly divided into three stages: the stage of reform and development, the stage of transition, and the stage of prioritizing ecological conservation and green development. Moreover, such changes jointly result from three factors: the major events, the focus of public opinions, and the care of the central government.

Discourse complex <i>i da</i> ‘and yes’ as a dialogue actualizer in modern Russian speech

The article examines semantic and pragmatic features of the discursive complex i da (“and yes”). The relevance of the research is explained by the active inclusion of i da in contemporary speech practice, various genres and styles over the past decade, which was not observed before. The novelty of the research lies in the fact that the element i da becomes the object of linguistic analysis for the first time. This study contributes to the understanding of the discursive complex i da in the context of modern linguistic practices. The findings of this research can be beneficial for further linguistic studies and practical applications. The element i da is not recorded in dictionaries and reference books, which also testifies to the novelty of the material presented in the article, which was extracted from the “National Corpus of the Russian Language”, the electronic media bank “Integrum”. The paper is also based to some degree on the personal observations of the authors. This study provides a fresh perspective on the linguistic element i da, contributing to the existing body of linguistic research. The research was conducted within the framework of the structural and descriptive method using semantic, syntactic, and contextual analysis. As a result, the main discursive role of the complex i da was established, i. e., maintaining the interactive nature of conversation through a ‘delayed response’ mechanism, which allows considering i da as a feedback marker. The discursive complex i da involves a real or potential (in the case of a monologue) interlocutor/opponent in the discourse, performing the role of a dialogic actualizer. The core seme of the complex (‘agreement’) can be explicitly supported by the context, and the addressee of the agreement can be not only the ‘other’ but also the speaker himself. The study reveals the rhetorical potential of i da in monologic speech. This research provides a comprehensive analysis of the discursive complex i da, highlighting its role in dialogic actualization and its rhetorical potential in monologic speech. The variants of punctuation design of the complex i da identified during the research indicate the need for its further study and the creation of a theoretical basis for subsequent codification in punctuation guides. The study proposes a hypothesis about the appearance of i da in Russian as a result of calquing English phrases and yes / and yeah, which are of international nature. This research emphasizes the importance of further investigation into the discursive complex i da, its punctuation variants, and its origins in the Russian language.

A comparative study on the perception of integrated resort in Korea before and after COVID-19 using social big data

The study was conducted to compare and analyze perceptions of integrated resorts before and after the outbreak of COVID-19 and to explore ways to revitalize the operation of integrated resorts that can be utilized in the post-Corona era. Keywords highly related to integrated resorts were collected from major social media and SNS channels in Korea, such as Naver, Daum, and Google. Unstructured big data analysis research was conducted using social network analysis and semantic network analysis, which are major methodologies for social big data. The keyword data collection period was divided into the time before and after the outbreak of COVID-19. A total of 7,933 keywords were collected before the outbreak, and 7,395 were collected during the period after the outbreak. The study included a total of 100 keywords, with 50 from each period. The research results showed that, first, before the outbreak of COVID-19, the keywords ‘Casino’, ‘Yeongjong-do’, ‘Hotel’, ‘Dream Tower’, ‘Incheon’, ‘Development’, ‘Domestic’, and ‘Business’ appeared with high frequency. After the outbreak, the keywords ‘Jeju’, ‘Resort’, ‘Dream Tower’, ‘Hotel’, ‘Inspire’, and ‘Business’ showed high frequencies of appearance. Second, CONCOR analysis confirmed the presence of seven keyword clusters before and after the outbreak of COVID-19. Based on the results of this study, various implications for integrated resorts that can be utilized in the post-Corona era suggested, along with future directions for integrated resort research.

Lexical Analysis of Japanese Children’s Songs from the Perspective of Japanese Language Education

Japanese children's songs can be a valuable resource for adult learners of the language, Firstly, the vocabulary used in children's songs is predominantly high-frequency and foundational, with a large portion falling below the N2 proficiency level. By mastering the words and phrases found in these songs, learners can expand their conversational abilities beyond the confines of traditional textbooks. Secondly, the songs offer a balanced representation of positive, negative, and neutral emotions, reflecting the emotional range and nuances of the Japanese language. This exposure to diverse emotional expressions can enrich learners' understanding of language and cultural nuances. Moreover, the study's semantic analysis reveals frequent word associations and co-occurrences, which can help learners grasp the interconnectedness of Japanese vocabulary and the cultural contexts in which words are used. Importantly, children's songs are deeply rooted in Japanese culture, indirectly exposing learners to various cultural aspects, such as the appreciation of nature, the concept of transience, and the importance of harmony and interconnectedness. This cultural immersion can foster a deeper understanding and appreciation of Japanese values and traditions. Furthermore, the familiar melodies and sing-along nature of these songs can facilitate social bonding and interpersonal connections among learners and native speakers. Engaging in shared cultural experiences, such as singing nursery rhymes together, can create a sense of community and strengthen the bond between learners and the target language culture.