Word Frequency Research Articles

A Systematic Review and Meta-Analysis of Factors Influencing Water Use Behaviour and the Efficiency of Agricultural Production in South Africa

Water use behaviour and efficiency are essential topics regarding water scarcity. Water is a life-sustaining resource used for various activities within the three primary sectors: agricultural, industrial, and domestic. Increasing competition among these sectors could affect the availability and sustainability of water use. The higher demand for agricultural-related commodities emphasizes the efficient and productive use of water. Still, to achieve this, the behaviour of consumers regarding water use needs to be changed. This systematic review paper aims to highlight the factors affecting water use behaviour and efficiency for agricultural production in South Africa. It further aims to determine how agricultural producers change their behaviour to improve their water use efficiency. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria were used as a reporting framework and guidelines to identify the articles included in the review. The review only included articles focussing on agricultural water use behaviour and efficiency and articles written in English and excluded articles from web pages, blogs, magazines, etc. The databases used for the review were Google Scholar and Web of Science. The articles were reviewed by the five authors to avoid the risk of bias, along with the inclusion and exclusion criteria. The final review included 30 peer-reviewed articles. A word frequency table was developed using the NVivo 14 software to conduct a thematic analysis for the review. The main factors which played a role in the water use behaviour and efficiency of farmers were (i) climate and adaptation strategies, (ii) policy and water pricing, and (iii) agricultural production and management. Each category elaborated on how water use could be improved and the different measures adopted to incorporate sustainable farm water use. This could be a guideline for farmers, stakeholders, and policymakers to improve and enhance water use behaviour and efficiency in Sub-Saharan Africa, particularly South Africa. This could ultimately assist in efficiently using the water while enhancing sustainability within the agricultural sector and attaining Sustainable Development Goal (SDG) six, which is to increase water use efficiency. The limitation of this study was that it was only narrowed down to the geographical context of South Africa. This review was funded by the Water Research Commission (WRC) of South Africa (Project Number: C20222023-00798). This review was not registered.

ANALYZING THE POLITICAL IDEOLOGIES OF TUN MAHATHIR IN TWO ERAS: A CORPUS-BASED ANALYSIS OF LEXICAL CHOICES

The ideology behind Tun Mahathir’s way of thinking always been the subject of interest for many. This research will investigate the political ideology of Tun Mahathir based on his lexical choices and words frequency in his speeches during two different Prime Minister eras and will compare the two corpora lexical choices, words frequency and political ideology that exist within.A total of 151 texts were compiled which consisted of 79 texts from the first era (2001-2003) and 72 texts from the second era (2018-2020). The comparative analysis of the two corpora were conducted through two stages, its word frequencies especially nouns to help determining lexical choices and Critical Discourse Analysis in revealing Tun Mahathir's political ideologies. The result shows some differences in word frequencies and lexical choices in both eras in which reflected Tun Mahathir's political ideology in the two eras. The word ‘negara’, a noun, has the highest frequency for both eras and yet words that were ''economy'' related has the highest frequency during the first era whereas society related was the highest during the second era. The changes in Tun Mahathir political party during the two eras may be a contributors to the changes of the lexical choices and slight changes of political ideology that occur. The changes in political landscapes and social problems in Malaysia contributes to the factor as well. Investigating Tun Mahathir's lexical choices in different speeches can help to investigate deeper into Tun Mahathir''s political ideology.

Mediumship and stylometry: Exploring a new way of attributing authorship to mediumistic writings

Stylometry is still largely unexplored for applications in attributing authorship to mediumistic writings, as outlined in the subsequent literature review. Stylometry is a statistical method for analyzing authorship with a history to detect anonymous authors, e. g., J. K. Rowling as the real author of The Cuckoo’s Calling. Modern stylometry transcends literature analysis, applying to forensic inquiries, such as plagiarism detection, online security, and group identity characteristics. Historically, stylometric research unfolds in three phases: focusing on single numerical functions, statistical methods based on word frequencies, and contemporary use of machine learning. Authorship analysis includes three primary objectives: authorship attribution, verification, and characterization. It uses mathematical linguistics, information theory, and linguistic features like vocabulary richness, word frequency, and syntactic structures. Stylometric methods reliably detect authorship in imitation scenarios (pastiche) and have now also led to adversarial stylometry, which facilitates and identifies attempts at anonymization. Distribution patterns of features such as function words or punctuation can only be detected with high computing power and appear to contain too little content or emotion to be recognized by psi abilities of mediums. Imitation on a stylometric level has not yet been achieved by professional writers and does not appear to be one of the abilities of savants either, whose left hemisphere, including speech and language, is the least developed, which is why such genuine talent cannot be assumed in mediums either. Due to its undeniable successes, its quantitative and computational approach, and its potential to investigate a wide range of research questions, stylometry therefore appears to be a desirable auxiliary science for mediumship research.

지방자치단체장의 정치성향별 지방자치단체 슬로건 변화에 관한 연구

This study is an analytical study on the changes of slogans of local governments. This study aims to confirm that whether the local slogans advocated by local governments can be influenced by the political inclinations of elected leaders. The scope of the study is local governments where the head of a local government was replaced by a different political party. Core vocabulary was derived from the frequency of words used in slogans and analyzed the values pursued and images emphasized by political orientation. Through comparative research, It was discovered that not only did the content of slogans change depending on the political leanings of the local government head, but also the design form of the slogans also changed. It was found that blue is often used in the slogans of local governments where progressive leaders had been in office, while local governments where conservative heads of organizations are elected often replace slogans using red. On the other hand, through an investigation of the words emphasized in their slogans, it was found that the common goal of local governments, transcending the trends of the times and political stances, is the happiness of local residents. It was confirmed that there is a need to improve the problem of the short life span of local government slogans due to the use of colors and word selection that show similarities with national administration, and to create and manage a viable slogan that can blend harmoniously into the overall city brand and meet the basic goals of regional development and the satisfaction of local residents.

AI 개입에 따른 디자인 씽킹 프로세스의 변화

The rapid evolution of Generative Artificial Intelligence with innovative technologies is making a significant impact within the Design Thinking Process. By using the ChatGPT-4 model from OpenAI, this study aims to evaluate the impact of Generative AI on design activities and establish a theoretical framework by reevaluating the Design Thinking Process. This paper conducts both quantitative and qualitative analyses. The quantitative analysis is performed using experimental surveys, word frequency, co-occurrence frequency, and CONCOR analysis, and the qualitative analysis is carried out through post-experiment interviews. The findings, derived from the comparisons of teams with and without prior Generative AI experience, highlight the positive impact of Generative AI on problem-solving, idea generation, and the convergence within UX design practices. Additionally, through the in-depth interviews with participants, it is possible to confirm the novelty and usability of Generative AI in the Design Thinking Process. The intervention of Generative AI in the Design Thinking Process promises substantial benefits for enhancing the roles of UX designers and a shift in traditional design thinking, by facilitating increased creativity and productivity in UX design tasks. There is a call for broader recognition and integration of these technologies to redefine the UX design process and its outcomes. For a more integrated approach within the UX design methodology, future research should aim to explore Generative AI's extensive applications and implications in design.

내러티브 과제 유형에 따른 초등 학령기 아동의 어휘 사용 특성

Background and Objectives: The vocabulary of an augmentative and alternative communication (AAC) system should reflect the AAC user’s needs and desires for successful communication. The selection of vocabulary should be based on the vocabulary used by the child’s peers. This study aimed to examine vocabulary usage characteristics of children in lower primary grades according to the type of narrative task and to select core vocabulary for use in an AAC system. Methods: We collected utterances from 20 children in lower elementary school for four narrative tasks (personal experience story, storytelling, explanation, and procedural descriptions). Characteristics of high-frequency vocabulary, core vocabulary, and word class vocabulary by task were examined. Results: Of the total number of words, the total frequency of core words was 77.28% (n = 26,400). The total number of other words was 2,677 (10.98%). The most frequent words in the core vocabulary were ‘-e(-에)’, ‘-ga(-가)’, and ‘-neun(-는)’. Conclusion: The inclusion of high-frequency words and core vocabulary in the narrative task can be used as a basis for vocabulary selection for school-aged children who use AAC systems.

Lexical Richness in Essays: A Corpus Based Study among Indonesian Junior High School Students

This study aims at analysing the lexical richness of junior high school students. Additionally, the aspects included in the analysis were lexical variation, lexical sophistication, lexical density, and the numbers of errors. The data were argumentative essays written by junior high school students Grade 9. The students are from one of the junior high schools in Kabupaten Tangerang. The data were analysed using a web concordance English v.9 named lextutor. The analysis reveal that the essays have a moderately high level lexical density and lexical variation. However, the students still relied on the 2000 most frequent words or K1 words with 68.29% of the total words. This study suggests that educators encourage their students to apply more word variation in their writings to improve the quality of their writings.

Research Trends Related on Hair Style in the Text Mining of Big Data Analysis

This study identified research trends by conducting keyword word frequency (TF), related word analysis (N-gram), and reverse document frequency (TF-IDF) through text mining, which analyzes text, which is unstructured data in big data, using the title and Korean abstract of domestic academic papers searched as hairstyles keywords in the Research Information Service (RISS). Through the research results, it was confirmed that hairstyles represent the characteristics of the times, and they are producing them or writing papers to understand preferences through statistics. The purpose of this study is to provide basic data to identify research trends through keywords extracted through text mining that analyzes text, which is unstructured data, in a new way with the development of big data processing technology.

COLOUR TERMS IN ASTROPHYSICAL TEXTS: A CORPUS STUDY

The aim of this paper is to present colour terms used by scientists in the field of astrophysics. We take into consideration both basic and non-basic colour terms – as understood by Berlin and Kay (1969). The research material, compiled in a corpus with AntConc, consists of abstracts published in selected astrophysical journals. The corpus size is 2,319,787 words. The most frequent basic colour term found in the abstracts is black (612 occurrences), followed by white (167), red (160), blue (111) and green (98). It appears that the frequent word combinations in which these and other colour words are used happen to be specialized terms whose formation involved metaphorical or metonymic processes, e.g. red giant, white dwarf, red planet, red noise and blue straggler.

Процессуальный код культуры в кабардинских пословицах и поговорках

The article examines the peculiarity of the implementation of the procedural code in Kabardian proverbs and sayings. The subject code is the most explored in linguistic study, allowing us to re-flect on numerous ideas that are important in people’s axiology. Due to the lack of research on the procedural codes of culture, the necessity of introducing these symbolic representations into the scientific field is justified. The aim of the study is to identify the semiotic elements of Kabardian paroemias that mark the value representations of native speakers. The scientific novelty consists in presenting the mechanisms of encoding the ethnomental paradigms of epistemology, in reflect-ing the deep structures of consciousness through words associated with the most important verbs of action. As a result of the study, the most frequent words projecting cultural dominants are iden-tified and their semantic classification is presented.

Language Identifier

This project presents a language identifier system focused on achieving high accuracy in identifying a specific set of 22 languages: Estonian, Swedish, English, Russian, Romanian, Persian, Pashto, Spanish, Hindi, Korean, Chinese, French, Portuguese, Indonesian, Urdu, Latin, Turkish, Japanese, Dutch, Tamil, Thai, and Arabic. Existing LI systems might struggle with the nuances of these languages, often prioritizing identification of more common languages. Our targeted approach allows for tailored optimization to achieve superior accuracy. We employ the Multinomial Naive Bayes (MNB) algorithm due to its effectiveness in text classification tasks and its ability to handle the high-dimensional, sparse features characteristic of LI based on character and word frequencies. The system achieves a promising accuracy of 95% using an 80/20 split for training and testing data. Keywords: Natural Language Processing (NLP), Language Identification (LI), Multinomial Naive Bayes (MNB), Text Classification, Language Barriers, Accuracy, Text Analysis.

Hypes in undergraduate thesis abstracts by Indonesian students across years

Previous studies showed that as a result of intense competition to succeed in academic pursuits such as publishing research papers and securing grants, promotional language known as hypes are pervasive in academic texts. This paper investigates hypes in a corpus of undergraduate thesis abstracts written by Indonesian English learners in a span of ten years, from 2011 to 2020. Taking a corpus-based approach, it examines the extent to which hypes are used in the thesis abstracts, including their linguistic manifestations, frequencies over the years, and the values they promote. We found hypes in all five moves of thesis abstracts, but they were most frequent in the introduction, in which they emphasized the importance and novelty of the research and stress the urgency of the research problems. In the span of the ten years, the frequencies of hypes generally increase, indicating the students’ awareness of the need to convince thesis supervisors, board of examiners, and their colleagues and the efforts to stand out in a competitive academic landscape. Important, investigate, and reveal were the most frequent hype words over the years and their instances suggest a growing emphasis on significance, a stronger commitment to evidence-based research, and desire to contribute new and concrete findings.

Implementation of an Automatic Meeting Minute Generation System Using YAMNet with Speaker Identification and Keyword Prompts

Producing conference/meeting minutes requires a person to simultaneously identify a speaker and the speaking content during the course of the meeting. This recording process is a heavy task. Reducing the workload for meeting minutes is an essential task for most people. In addition, providing conference/meeting highlights in real time is helpful to the meeting process. In this study, we aim to implement an automatic meeting minutes generation system (AMMGS) for recording conference/meeting minutes. A speech recognizer transforms speech signals to obtain the conference/meeting text. Accordingly, the proposed AMMGS can reduce the effort in recording the minutes. All meeting members can concentrate on the meeting; taking minutes is unnecessary. The AMMGS includes speaker identification for Mandarin Chinese speakers, keyword spotting, and speech recognition. Transferring learning on YAMNet lets the network identify specified speakers. So, the proposed AMMGS can automatically generate conference/meeting minutes with labeled speakers. Furthermore, the AMMGS applies the Jieba segmentation tool for keyword spotting. The system detects the frequency of words’ occurrence. Keywords are determined from the highly segmented words. These keywords help an attendant to stay with the agenda. The experimental results reveal that the proposed AMMGS can accurately identify speakers and recognize speech. Accordingly, the AMMGS can generate conference/meeting minutes while the keywords are spotted effectively.

Dialectical-Relational Approach on Profanity Words among Muslim Students

Speaking in good manner is highly advised in Islamic teaching, but this notion had been challenged by socio-cultural values of the kinds if profanity words circulating among Muslim students. As qualitative research, this research aimed to investigate the discourses related to the use of profanity words among Muslim students from the perspective of the Dialectical-Relational Approach (DRA). The first was to discover the most frequent profanity words uttered by Muslim students, the reasons for using profanity words which were classified as propositional and non-propositional, and how DRA perceived the use of profanity words influenced their identity as Muslim. In this research, a questionnaire was chosen as the primary instrument, which consisted of a set of profanity words by Chirs Kirk, and the respondents’ reasoning for using profanity words. The respondents were 14 students from a private Islamic-based university in Indonesia. The result had shown that the students chose two profanity words as the most popular: shit and fuck. Meanwhile, the most dominant reason for using profanity words was to relieve tension which belonged to the non-propositional aspect. DRA perceived the complexity of profanity words among Muslim students and the use of profanity words emphasized the socio-cultural aspect of language, yet, Islamic teaching encouraged the use of good-mannered utterances because it might alter people’s opinion about Islam negatively. Thus, the researchers perceived the use of profanity words as a complex phenomenon that encompasses various contexts.

Indonesian Slang Word Formation Processes in TikTok

Language changes over time due to social and cultural factors. These changes are evident through language varieties such as standard and non-standard languages, dialects, accents, and registers. This research focuses on one type of language variation, namely slang. Slang words show that language is constantly changing. For example, there are many new slang words that emerge and old ones that are no longer used or replaced. Slang also reflects people’s creativity because through slang we can see how someone can be very creative in making new words or modifying existing words. This research aims to identify the slang words that appear in the comments section of the TikTok during June to December 2022 and analyze the word formation process of each slang found. The authors used the qualitative descriptive method in order to present the data thoroughly. This study found that there were 39 slang words that appeared repeatedly and there were six most common word formation processes found in TikTok comments, namely blending, clipping, borrowing, acronym, affixation, and multiple processes. The most frequent processes are blending and clipping. The least frequent word formation processes are affixation and borrowing.

Strategi Kampanye Partai Amanat Nasional Pada Pemilu Legislatif 2024: Pendekatan Teori Marketing-Mix

This article examines to find out the successful campaign strategy of the National Mandate Party (Partai Amanat Nasional, PAN) in increasing its vote in the 2024 Legislative Election. Methodologically, this article uses qualitative method by applying case study approach. In data gathering, it employs library research by mining data from online news channels. In the data analysis, it utilizes the modern platform of NVivo 14 mainly word frequency query. To measure the campaign strategy of PAN, this article applies four indicators of marketing-mix theory: product, price, place, promotion (4P). The finding reveals that in terms of product, PAN promotes a platform of “helping people” with its past record as the reformist party and supported by the legislative candidates’ background of entrepreneurs and artists-celebrities. Regarding the price, the PAN’s campaign budget spent at least 223 billion IDR with its successful campaigns which conducted by each legislative candidate. PAN prefers to rely on the popularity of President of Joko Widodo and legislative candidates. In the context of place, the strategy of local network and canvassing are based on the creativity of each legislative candidates in attracting voters’ sympathy. The leader tour is conducted by visiting influential public figures. Concerning promotion, the campaign publication of PAN relies on printed mass media, television, and social media while event publication is carried out in various regions across the country. Among those four indicators, the price has the most significant impact which causes to the successful campaign of PAN in the 2024 Simultaneous Election.

Revisiting the automatic prediction of lexical errors in Mandarin

Abstract Speech errors provide cues for explaining the process of word retrieval. For example, speech errors are less likely to occur with high-frequency words since these words already receive a high level of activation. The current analysis further develops existing findings in two ways. First, instead of considering the overall frequency of the words in the entire corpora, we consider the gap in frequency between sequential pairs of words. We hypothesize that speech errors are more likely to occur if the target has a much lower frequency than its preceding word. Second, we use word embedding methods to quantify the semantic distance between sequential pairs of words. We hypothesize that speech errors are more likely to occur with words that have a large semantic distance from their preceding context. We also consider the potential effects of phonetic distance between sequential pairs of words and position-in-utterance of words in utterances. The results from a Mandarin corpus of speech errors show that word frequency and semantic distance between sequential pairs of words can be used to predict the occurrence of speech errors with an accuracy above the majority baseline.

Getting a handle on a Hansard with Python and NLTK, or how to tame the linguistic picture of British politics with NLP

The article proposes an optimised starter’s set of basic Python and NLTK (Natural Language Toolkit) methods that are essential in the analysis of massive textual corpora conducted as part of research investigating linguistic images of the world. The need to specify and detail these applied techniques stems from the nature and scope of the inexorable challenges confronted by contemporary cognitive linguistics and lexicology in the realm of unstructured big data analysis. Their viability and practical value are demonstrated in a series of illustrative examples where they are applied to the processing of continuous parallel diachronic corpora of Hansard that capture the discourse of both chambers of the British parliament produced in the years 2006-2023 and jointly amounting to over a third of a billion tokens.The article suggests that the methods it outlines and classifies can be seen as forming an indispensable minimum of IT competences that is capable of delivering a substantial boost to the level of research both as regards its overall quality and its competitive edge. The proposed toolkit includes an essential set of instruments for target vocabulary processing as well as for the assessment and visualisation of word and phrase frequency and collocation.The author presumes that, urged by the need to keep abreast of prevailing trends, the contemporary Russian researcher of linguistic images of the world is highly likely to find themselves compelled at some point to embrace the quantitative analysis methods made possible by combining Python and NLTK. As part of its substantial and varied range of benefits, the latter would arguably help them design and customise research protocols, adapting them with ease and versatility. Lastly and most importantly, the author suggests that Python and NLTK skills may serve as a comfortable gateway towards eventually upgrading one’s linguistic research to cutting-edge global standards of technological sophistication and marketability.

Delineating Landscape Features Perception in Tourism-Based Traditional Villages: A Case Study of Xijiang Thousand Households Miao Village, Guizhou

This study is a feature perception study of traditional village landscapes, refines the research method of traditional village landscape features using tourists online comment data, combs the landscape perception features of Xijiang Thousand Households Miao Village from tourists perspectives, digs out the managers’ problems in landscape planning, protection, utilisation, and puts forward the corresponding improvement strategies. In this paper, the Octopus data collector was used to collect online evaluation data from nine target platforms, and ROST CM6 was used to analyse the data for word frequency analysis, semantic network analysis, and sentiment analysis. Finally, using Nvivo12, the data was coded and a multidimensional model of landscape perception was constructed: natural landscapes, cultural and social landscapes, perceived landscapes, seasonal landscapes, and services and infrastructures. The results show that in the landscape perception model, the cultural and social landscape modules are the core factors affecting tourists’ psychological perceptions, with most tourists holding positive emotions towards the scenic spots and a few negative emotions mainly focusing on the relatively weak natural landscape, the unsatisfactory road system and charging system, and the over-commercialised development. In response to these problems, this study proposes corresponding planning recommendations. The results of the study reflect the trend of deep integration of culture and tourism in traditional villages in China, respond to the policy guidance of China’s rural revitalisation policy, and provide useful references and insights for the landscape construction and development of the Xijiang Thousand Households Miao Village and even similar tourist-oriented traditional villages.

A Stylometric Glance at Novels in Euskara

While Basque has been posited as possibly the oldest existing language on the European continent, it appears in written form only in the sixteenth century. The first Basque novel emerges over 300 years later and to this day the genre lacks exhaustive research. The article sets as its aim a stylometric analysis of selected twentieth- and twenty-first-century Basque novels, sourced from the online platforms Armiarma and Booktegi. These are analyzed based on the frequency of the most frequent words measured using cluster analysis and set against a backdrop of foreign novels translated into Euskara. The results show that the originals in Euskara remain distinct from translated works, pointing to the unique linguistic character of the Basque novel. Some linguistic patterns potentially responsible for this distinction are presented. The results are visualized on a map revealing the chronological evolution and the contribution of the Basque novel to the broader literary landscape.