Semantic Content Analysis Research Articles

Evaluation of Studies Examining the Problems of Novice School Administrators: A Meta Synthesis Study

Purpose: This study aims to evaluate the studies examining the problems of novice school administrators in Türkiye by using a meta-synthesis method.
 Design/Methodology/Approach: The population of the current study, which was conducted using semantic content analysis (semantic analysis), consists of studies on the problems of novice school principals indexed in YÖKTEZ (Council of Higher Education, National Thesis Centre), Google Scholar, EBSCOhost, TÜBİTAK ULAKBİM Social and Human Sciences Database and DergiPark databases. The data sources or materials of the research consist of 9 studies (4 theses and 5 articles) determined by using the criterion sampling method, one of the purposeful sampling methods.
 Findings: Five themes were obtained as a result of the research, which are listed as administrative problems, problems related to internal stakeholders of the school, problems related to external stakeholders of the school, problems related to school business and management, situational factors.
 Highlights: The results of the research reflect that novice school administrators face various problems not only in terms of administration but also with the internal and external stakeholders of the school. Therefore, reducing the problems faced by novice school administrators requires an initial addressing of the necessary arrangements for school administration to be a career profession based on competence and merit with a holistic perspective in the selection, placement, appointment and assignment of educational administrators.

Hegemoni Kelas Menengah Atas Pada Buku Teks: Studi Analisis Dominasi Kelas Atas Terhadap Kelas Bawah Pada Buku Teks TK B

This study aims to find out how far the upper middle class dominates the lower class and to find out and analyze the narratives built in textbooks when interacting with the lower class. This research uses qualitative research based on library research, where the source of data used as research material is Kindergarten B textbooks. The data is analyzed using content analysis, namely; pragmatic content analysis, semantic content analysis, and analysis of sign means. The results of the study show that the dominance of the upper middle class over the lower class is drawn through lifestyles, such as; vacation to the beach, sitting on soft sofa chairs, diving, and so on. The narrative developed in the Kindergarten B textbook focuses more on urban lifestyles and the balancing narrative that can fit into the upper and lower middle social class is not too significant. Or in another language not apple to apple. Keywords: Hegemony, Upper Middle Class, Textbooks

Austrian women's associations in the educational press of the dualism era

In the present paper, Austrian women's associations and associations will be reviewed in the spirit of women's emancipation. During this period, many women's societies, associations, foundations and clubs were established in the territory of the Monarchy, with a very wide range of goals. In my study, I present the main Austrian women's societies in the light of the Austrian pedagogical journals of the dualism era, in the period from 1889 to 1910. In the research, I looked for the answer to the question: how often and from what perspective did the journalists and educational specialists of the time write about the necessity and usefulness of women's associations in the various pedagogical magazines? What concerned writers, teachers, and readers in relation to the activities of women's associations at the time? In the course of the research, I examined 3177 coded units of four types of Austrian educational newspapers from the era of dualism (Österreichische Lehrerinnen-Zeitung; Der Lehrerinnen-Wart and its successors: Neuzeit, Frauenleben, Neues Frauenleben; Frauen-Werke; Mittheilungen des Vereines der Lehrerinnen und Erzieherinnen in Österreich) and processed it using the method of semantic content analysis, including naming analysis.

The potential to develop environmental values on privately owned forest land in southern Sweden

ABSTRACT Private forest owners’ management decisions significantly impact the development of forest values in Sweden. This study explored the potential to develop environmental values on privately owned land in southern Sweden. Data were collected through interviews with 23 forest owners and analyzed with semantic content analysis. The interviewees owned estates of productive, predominantly coniferous forest ranging in size from 10–825 ha. They were aged 36–84, and 26% were female. Results showed that there is considerable potential to develop environmental values on private land since 1) Forest owners demonstrated multi-functional views of primarily social and emotional dimensions surrounding forest ownership, and the mindset of combining goals enables many different values to be developed, 2) Desired management showed numerous ideas that could bring a diversity of benefits, and 3) Practical management included various production-favoring measures, but even more for environmental, social, cultural, and emotional purposes that, largely unnoted, bring environmental conservation benefits. All forest owners perceived barriers to management and ownership, categorized primarily to structural or surrounding society factors. Financial incentives, policies encouraging forest owners’ initiatives, an adequate supply of resources and sound management advice are suggested measures to reduce barriers and facilitate the development of environmental values.

Sağlık Bilgi Yönetiminde Kariyer İçin Gerekli Uzmanlık Rollerinin ve Beceri Setlerinin Tespit Edilmesi

This study aims to investigate the competency areas and skill sets demanded on the job market for health information management (HIM), which plays a vital role in sustaining and enhancing the quality and efficacy of health services. In accordance with this objective, a semantic content analysis was performed on online HIM job postings using a quantitative method based on text mining and probabilistic topic modeling to identify the expertise roles and skill sets as semantic topics. Our findings revealed ten expertise roles and twenty-four skills that represent a broad spectrum of HIM professions’ competency requirements. “Specialist” (17.57%), “Director” (17.05%), “Manager” (13.18%), “Coder” (12.40%), and “Technician” (11.11%) are the top five expertise roles for HIM. A competency taxonomy was developed for HIM professions based on the knowledge and skills revealed by 24 topics using topic modeling analysis. The HIM competencies were categorized as “Medical Knowledge” (39.92%), “Management Skills” (29.80%), “IT Skills” (16.09%), and “Soft Skills” (14.18%). Our findings may have significant implications for HIM candidates and professionals, healthcare industries, and academic institutions in their efforts to comprehend, evaluate, and develop the necessary competencies and skills for HIM careers.

Gender-Inclusive Textisms: How Spanish-speaking educational communities promote linguistic innovations on twitter

Any linguistic reform aimed at gender equality benefits from teacher's capacity as spreaders, and literature has shown that Twitter can be used as an excellent channel for the dissemination of good practice in language use. In a mixed-methods study based on public data mining and semantic content analysis, we examine how teachers use gender-fair language (GIL) in their digital communications on Twitter, what GIL procedures they use and, if Spanish digitalk incorporates specific textisms for GIL. Results confirmed that teachers make a widespread use of GIL procedures, prefer the use of collective nouns as a GIL mechanism, and intentionally incorporate GIL into digitalk through specific textisms, what we have named gender-inclusive textisms (GIT). The findings indicate that teachers are at the forefront of gender-inclusive language activism in educational virtual communities, and therefore, that although Twitter may contain messages that outrage the dignity of individuals, it is also a privileged space for linguistic innovations oriented toward gender equality.

What issues are data scientists talking about? Identification of current data science issues using semantic content analysis of Q&A communities.

Because of the growing involvement of communities from various disciplines, data science is constantly evolving and gaining popularity. The growing interest in data science-based services and applications presents numerous challenges for their development. Therefore, data scientists frequently turn to various forums, particularly domain-specific Q&A websites, to solve difficulties. These websites evolve into data science knowledge repositories over time. Analysis of such repositories can provide valuable insights into the applications, topics, trends, and challenges of data science. In this article, we investigated what data scientists are asking by analyzing all posts to date on DSSE, a data science-focused Q&A website. To discover main topics embedded in data science discussions, we used latent Dirichlet allocation (LDA), a probabilistic approach for topic modeling. As a result of this analysis, 18 main topics were identified that demonstrate the current interests and issues in data science. We then examined the topics' popularity and difficulty. In addition, we identified the most commonly used tasks, techniques, and tools in data science. As a result, "Model Training", "Machine Learning", and "Neural Networks" emerged as the most prominent topics. Also, "Data Manipulation", "Coding Errors", and "Tools" were identified as the most viewed (most popular) topics. On the other hand, the most difficult topics were identified as "Time Series", "Computer Vision", and "Recommendation Systems". Our findings have significant implications for many data science stakeholders who are striving to advance data-driven architectures, concepts, tools, and techniques.

Why am I so successful? Self-presentation and deliberative attributions of success in entrepreneurship

This study explores the complexities of causes of success mentioned in entrepreneurs' narratives in a broadcasted context. Building on strategic self-presentation and attribution theories, we employed inductive methods to map the configurations of public narratives explaining entrepreneurial success. The data analyzed were gathered from 173 reflective interviews featuring entrepreneurs on the United States' National Public Radio, using machine learning techniques for semantic content analysis. The results show that entrepreneurs can adopt three strategic presentation narratives to explain success in entrepreneurship. Significantly different patterns emerge in the three strategic narrative configurations. First, “lucky charming” narratives reflect an ingratiation strategy, mentioning external and uncontrollable causes of success to increase the entrepreneurs’ likability for the audience. Second, “work striving” narratives use self-promotion strategies to push for recognition of accomplishments, efforts, and intellectual abilities. Third, “social connecting” narratives simultaneously make use of ingratiation and exemplification strategies, including capitalizing on the positive signals given by the social support attracted during their entrepreneurial journey. These three discourse patterns have implications for influencing reputation and driving business- and personal-related outcomes. The findings provide a better understanding of deliberate appearances by entrepreneurs in broadcast contexts and tools for nascent entrepreneurs to leverage their role models among those with acclaimed entrepreneurial success.

Differentiating between epileptic and functional/dissociative seizures using semantic content analysis of transcripts of routine clinic consultations

The common causes of Transient Loss of Consciousness (TLOC) are syncope, epilepsy, and functional/dissociative seizures (FDS). Simple, questionnaire-based decision-making tools for non-specialists who may have to deal with TLOC (such as clinicians working in primary or emergency care) reliably differentiate between patients who have experienced syncope and those who have had one or more seizures but are more limited in their ability to differentiate between epileptic seizures and FDS. Previous conversation analysis research has demonstrated that qualitative expert analysis of how people talk to clinicians about their seizures can help distinguish between these two TLOC causes. This paper investigates whether automated language analysis - using semantic categories measured by the Linguistic Inquiry and Word Count (LIWC) toolkit - can contribute to the distinction between epilepsy and FDS. Using patient-only talk manually transcribed from recordings of 58 routine doctor-patient clinic interactions, we compared the word frequencies for 21 semantic categories and explored the predictive performance of these categories using 5 different machine learning algorithms. Machine learning algorithms trained using the chosen semantic categories and leave-one-out cross-validation were able to predict the diagnosis with an accuracy of up to 81%. The results of this proof of principle study suggest that the analysis of semantic variables in seizure descriptions could improve clinical decision tools for patients presenting with TLOC.

Analysis of Sidoarjo Health Office Instagram Content as a Covid-19 Information Media

This study aims to determine the semantic content analysis on Instagram @dinkes_sidoarjo as a medium of information on covid-19 for the people of Sidoarjo in August 2021. The research is based on the popular social media, namely Instagram. regarding covid-19. This makes the post and caption on Instagram @dinkes_sidoarjo whether it has become a medium of information for the people of Sidoarjo. This research method uses qualitative and data collection in the form of documentation as many as 18 posts. This data analysis uses semantic content analysis, which is analyzed by designation, characterization, and statement analysis. The results show that @dinkes_sidoarjo is more directing the reader and is more about discussing the map of the spread of covid-19 in an area which was repeated 132 times in August 2021. This can be interpreted that as a medium of information @dinkes_sidoarjo in his post does not discuss covid-19 education and Covid-19 vaccination activities as an effort to reduce the risk of transmission in August 2021

Многопараметрическая психологическая диагностика склонности к газлайтингу в межличностных отношениях

The article focuses on the study of the main psychometric characteristics of the author's questionnaire for assessing the propensity to gaslighting in interpersonal relationships. A multiparametric approach to the psychodiagnostics of the phenomenology of gaslighting is defined as the subject of scientific research, the goals are to develop a diagnostically significant model for assessing the propensity to gaslighting in interpersonal relationships, implementing it in the questionnaire of the same name with its subsequent approbation. The research methodology was based on axiological, humanistic, activity and polysubject approaches in psychology, relationship theory and deviantology. Semantic content analysis, expert survey, psychological testing, self-assessment were used at different stages of scientific research. The total volume of the empirical sample was 165 people (including 17 experts and 148 subjects). Mathematical and statistical data processing involved the calculation of descriptive statistics and correlation analysis, which was implemented in MS Excel and IBM SPSS Statistics v 27 software products.
 Based on the results of theoretical and analytical research, a six-parametric gaslighting model was developed, which was the basis for the corresponding questionnaire. The measuring framework of the methodology and the degree of severity of gaslighting is formed by six private scales: 1) «behavioral intolerance»; 2) «expressive dominance»; 3) «projection of personal problems»; 4) «intrigue» (manipulation); 5) «verbal-behavioral discongruence»; 6) «devaluation of the other», from which an integral indicator is formed. During the psychometric study of the questionnaire, its high criterion validity was confirmed – statistically significant correlations with self-assessments of the same name were established (Rs = 0.42-0.63 at p=0.01). It is assumed that the technique has a good diagnostic potential, and can be used to study the phenomenology of gaslighting. Innovative are: the stimulus material of the questionnaire, the description of diagnostic scales, psychometric parameters of the methodology. The material makes it possible to provide psychodiagnostics with innovative diagnostic tools that provide solutions to a wide range of tasks in the field of not only psychodiagnostics, but prevention, assistance and correction

Public Attitudes Toward Anxiety Disorder on Sina Weibo: Content Analysis.

Anxiety disorder has become a major clinical and public health problem, causing a significant economic burden worldwide. Public attitudes toward anxiety can impact the psychological state, help-seeking behavior, and social activities of people with anxiety disorder. The purpose of this study was to explore public attitudes toward anxiety disorders and the changing trends of these attitudes by analyzing the posts related to anxiety disorders on Sina Weibo, a Chinese social media platform that has about 582 million users, as well as the psycholinguistic and topical features in the text content of the posts. From April 2018 to March 2022, 325,807 Sina Weibo posts with the keyword "anxiety disorder" were collected and analyzed. First, we analyzed the changing trends in the number and total length of posts every month. Second, a Chinese Linguistic Psychological Text Analysis System (TextMind) was used to analyze the changing trends in the language features of the posts, in which 20 linguistic features were selected and presented. Third, a topic model (biterm topic model) was used for semantic content analysis to identify specific themes in Weibo users' attitudes toward anxiety. The changing trends in the number and the total length of posts indicated that anxiety-related posts significantly increased from April 2018 to March 2022 (R2=0.6512; P<.001 to R2=0.8133; P<.001, respectively) and were greatly impacted by the beginning of a new semester (spring/fall). The analysis of linguistic features showed that the frequency of the cognitive process (R2=0.1782; P=.003), perceptual process (R2=0.1435; P=.008), biological process (R2=0.3225; P<.001), and assent words (R2=0.4412; P<.001) increased significantly over time, while the frequency of the social process words (R2=0.2889; P<.001) decreased significantly, and public anxiety was greatly impacted by the COVID-19 pandemic. Feature correlation analysis showed that the frequencies of words related to work and family are almost negatively correlated with those of other psychological words. Semantic content analysis identified 5 common topical areas: discrimination and stigma, symptoms and physical health, treatment and support, work and social, and family and life. Our results showed that the occurrence probability of the topical area "discrimination and stigma" reached the highest value and averagely accounted for 26.66% in the 4-year period. The occurrence probability of the topical area "family and life" (R2=0.1888; P=.09) decreased over time, while that of the other 4 topical areas increased. The findings of our study indicate that public discrimination and stigma against anxiety disorder remain high, particularly in the aspects of self-denial and negative emotions. People with anxiety disorders should receive more social support to reduce the impact of discrimination and stigma.

What is a retail brand - a systematic review of terms and definitions

PurposeAlthough many scholars have acknowledged inconsistencies in the use of the retail brand term within the existing empirical literature, no one has conducted a systematic study to clarify the confusion of terms. Aiming at unifying the use of terms, this study aims to explore the terms that best express each retail brand concept, and discusses the definitions of proposed terms that can distinguish the connotation of different retail brand concepts.Design/methodology/approachThrough a systematic review, 463 articles were obtained, from which retail brand terms and their definitions were further extracted. Semantic analysis and content analysis were adopted to analyze terms and definitions, respectively.FindingsSemantically, the terms that best express four levels of retail brand concepts are own product brand, store brand, platform brand and retailer brand. Six key elements to distinguish different levels of a retail brand are identified through the content analysis of definitions, and on this basis, four proposed terms are defined.Originality/valueNoting that no study focuses on the conceptual confusion of retail brands in recent decades, the findings are expected to clarify the confusion of terms and unify the use of terms, hence facilitating the communication between scholars and the sharing of research results.

Unexpectedness as a Measure of Semantic Learning When Training Transformer Models

Many problems in NLP such as language translation and sentiment analysis have shown a lot of improvement in recent years. As simpler language problems are solved or better understood, the focus shifts to more complex problems such as semantic analysis and understanding. Unfortunately, a lot of studies in the literature suffer from a too much specificity problem. The algorithms and datasets are too domain specific. In this study, we analyze and elaborate on this notion of generality. Instead of selecting a highly specialized data set for semantic analysis, we take a generic and possibly dry data set, and we study how a plain vanilla Transformer performs in learning higher level semantic patterns beyond what was obvious or expected. We tune our Transformer model on a classic language task to ensure correct performance. Once tuned, the goal is to select sentences with specific key words and study whether higher level semantic patterns may have been learned by our model. We believe that we obtained promising results. The average BLEU score for sentences less than 25 words is equal to 39.79. Our initial qualitative analysis of possible semantic content of interest shows a 17 percent rate in finding interesting semantic patterns. We provide discussion of data driven results of unexpectedness as a measure of semantic learning.

Conceptualization of green curriculum in Iran's higher education system

Today, the world is facing various environmental hazards as a result of non-standard human activities, and different societies are forced to find solutions to manage and solve them. Universities are one of the significant social institutions in every society, which generally take on special duties when a crisis occurs. Regarding the management of environmental risks, one of the tasks assigned to universities is to implement the idea of a green university, which has often been implemented in different parts of the world in the form of greening the physical environment of the university. While green education in general and green curriculum in particular can increase the effectiveness of universities' activities in this field. Hence, this qualitative research aimed to conceptualize the green curriculum in Iran's higher education system. The population was the curriculum experts who have been active in the field of sustainability and environmental management. Moreover, a collection of authentic scientific papers related to the research objectives were also used in order to further enrich and complete the data. Data analysis was done through semantic content analysis. The results led to extraction of 47 codes related to the concept of the green curriculum. Accordingly, the concept of green curriculum can be categorized in three dimensions: concepts aimed at the society, concepts aimed at the learning ecosystem, and concepts aimed at the classroom and learners.

Функционирование причастных форм в ламунхинском говоре эвенского языка

The article considers the participial forms of the verb in the Lamukhinskiy dialect of the Even language. The Lamu-khinskiy dialect is understandable to most speakers of the Western dialect of the Even language spoken in Yakutia. The Lamukhinskiy dialect is prevalent in the territory of the Kobyai district of the Republic of Sakha (Yakutia) within the villages of Sebyan-Kyuel and Segyan-Kyuel. This idiome is currently among the most prosperous Even dialects with a higher vitality in terms of functioning parameters and social indicators: about 800 people regularly communicate in it, with intergenerational transmission preserved in the area of the language community. A detailed examination of the most commonly used verbal forms, i.e., the participles in the Lamukhinskiy dialect, is necessary to complete the data on specific issues of morphology and syntax in Tunguso-Manchu linguistics. In contrast to other Eastern and Western dialects, the composition of participial forms in the dialect under consideration is much broader. This study has identified for the first time the use of previously unidentified participles of the following actions: obligatory, passive, and possible with obligatory meaning. The analysis of morphological criteria and semantic content identified the perfect participle and the participle of convenience for performing an action. The article presents the author’s version of the classification of the Even dialects, including the Lamukhinskiy dialect. The study was performed based on the field materials collected by the author.

Development of the Item-Conformity Method for Japanese questionnaire about self Ⅴ - Validity and Reproducibility of Semantic Content Analysis of Sentences -

Development of the Item-Conformity Method for Japanese questionnaire about self Ⅴ - Validity and Reproducibility of Semantic Content Analysis of Sentences -

A comparative study of positive and negative electronic word-of-mouth on the SERVQUAL scale during the COVID-19 epidemic - taking a regional teaching hospital in Taiwan as an example

BackgroundIn recent years, studies have shown that electronic WOM (eWOM) directly reflects consumers’ post-purchase psychological perception and directly affects repurchase behavior. This information is valued by institutions in various fields. Within the scope of the evaluation of service characteristics, medical service is the least visible and most difficult service attribute to evaluate. Service organizations must have high trust attributes. Therefore, an eWOM review significantly influences people’s decision-making process when choosing a healthcare provider. The purpose of this research is to combine eWOM reviews with the SERVQUAL scale in a comparative study of positive and negative eWOM reviews of a regional teaching hospital in Taiwan.MethodsThis research obtained data from publicly available eWOM reviews on Google Maps of a regional teaching hospital in Taiwan over the past 10 years (from June 24, 2011, to December 31, 2021) using website scraping technology. The semantic content analysis method was used in this study to classify eWOM reviews according to the revised PZB SERVQUAL scale.ResultsStatistical analysis was conducted. During the COVID-19 pandemic, positive reviews showed a downward trend. Among the five determinants of the SERVQUAL of PZB, positive eWOM reviews performed best in “assurance” with a positive review rate of 60.00%, followed by 42.11% for “reliability”. For negative eWOM reviews, “assurance” performed the worst with a positive rate of 72.34%, followed by “responsiveness” at 28.37% and “reliability” at 26.95%.ConclusionSince the onset of COVID-19 in 2020, negative eWOM has increased significantly and exceeded the amount of positive eWOM. Regardless of positive and negative reviews, what patients care most about is “assurance” of the professional attitude and skills of medical staff, which urgently needs to be strengthened. In addition, good “reliability” will help to develop positive eWOM. However, “responsiveness” as indicated by poor service waiting time can easily lead to the spread of negative eWOM. Hospital management should focus on these service-oriented qualities.

Parental well-being: Russian women's view

The article presents the results of a qualitative sociological study using the author's technology in order to conceptualize the phenomenon of parental well-being. The methodology of the study is based on the generalization of the theoretical provisions of parenthood and family well-being. It is concluded that parental well-being as a factor of demographic processes has not been studied enough, the concept of parental well-being has vague contours, there is no detailed formulation of its content and basic elements. In May — July 2022, on the results of an online survey there were collected and processed empirical data based on the responses of women (N = 335) to the open question "What do you associate with the concept of "parental well-being"? Write one or two phrases/sentences." The respondents' responses were processed using semantic content analysis. The word "happiness" was used in 18.8% of the responses received. Thematic coding was applied, individual and collective trajectories of meanings were identified. There are 10 collective trajectories combined in the author's system of markers of parental well-being. The frequency of markers mentioning in women's responses was calculated, that made it possible to identify key, basic markers: relationships with children (32.5%); well-being and success of children (29.6%); health (28.4%); security: income, work, housing (19.1%); emotional state of parents (10.4%); time (8.4%). Childless women were 3 times less likely to mention the topic "Well-being and success of children", but they are much more likely to associate parental well-being with finances and the ability to provide everything necessary for children. It makes sense to take these results into account when forming programs to popularize parenthood among young people. The author has formulated a "working" definition of the concept of parental well-being, substantiated the need for further research to clarify it on the basis of surveys of men using a similar technology. The practical value of the system of basic markers of parental well-being lies in the possibilities of its application for further development of the sample survey program "Digitalization of employment, fertility and parental well-being".

A methodological proposal integrating the translation process into the study of cognitive effort

This paper presents a methodological proposal that integrates the translation process into studying the cognitive effort with the use of three instruments. Data triangulation accounts for such phenomena. Translation process research has used Translog to approach mental activities, such as cognitive effort. However, authors such as O’Brien (2006) suggest the use of complementary methods to have a comprehensive understanding of what occurs while translating. This paper aims to present a data collection model that includes the use of Translog as the main instrument to record the indicators of cognitive effort (time and typing pauses) during a translation process, a screen capture software that records the screen’s output, as well as retrospective interview to obtain verbal information from its users. In order to establish a relationship between cognitive effort and the translation process, a triangulation data method was used with the information collected from the aforementioned instruments, alongside conducting a semantic content analysis.