Textual Analysis Research Articles

General and Substantive Accountability in Nursing Home Services: Assessing Messages from the Demand Side and the Supply Side

ABSTRACT This study examines the extent to which general and substantive accountability is integrated into the language used by key actors involved in nursing home services. Particularly, we investigate the messages used by the supply side, which includes public and private organizations involved in residential care for older adults, and the demand side, which comprises organizations representing service beneficiaries. Moreover, we explore the alignment between the messages used by both sides of the accountability relationship. In the context of Spanish nursing homes, we analyzed a corpus of tweets by organizations from both sides of the accountability relationship, from one year before the outbreak of COVID-19 restrictions to after their implementation. Using text analysis techniques, we found that messages related to general and substantive accountability had a low priority before and after the outbreak. Public organizations were slightly more likely to employ general accountability terms than private organizations. This is particularly in non-crisis situations, although less frequently than organizations representing beneficiaries. Our analysis demonstrates a lack of convergence between the messaging on the supply and demand sides, indicating a communication breakdown between the two sides in the accountability relationship.

Information Seeking and Receiving of Older Adults with Diabetes in the Online Health Community: An Information Need Contextualization Perspective

ABSTRACT Online health communities (OHCs) are important online health communication channels for older adults with diabetes to access health information. When seeking health information, they often disclose a variety of contextual information (e.g., socio-economic situations) in their questions. Selective contextual information disclosure is a type of communication strategy for users in OHCs to elicit replies from others. In this study, we adopted text analysis to investigate what contextual information older adults with diabetes disclose to articulate their information needs and used the fixed-effect Poisson model to examine the relationships between different types of contextual information disclosure and informational support receipt. Our analyses were based on a dataset of 4,505 questions and corresponding replies from an online diabetes community. The results showed that cognitive information is the most frequently disclosed contextual information, while older adults tend to disclose demographic information in their questions less. Providing demographic and situational details in questions can enhance informational support receiving, resulting in an increased number of informational supports. However, disclosing cognitive, affective, informational channels, or support information does not significantly affect the informational support receiving. These findings can contribute to extending our existing understanding of information seekers’ communication strategies in OHCs.

THE STUDY OF COMPARISON OF SINGLE-INCISION LAPAROSCOPIC VERSUS CONVENTIONAL LAPAROSCOPIC APPENDECTOMY: A COMPREHENSIVE SYSTEMATIC REVIEW

Background: Acute appendicitis is highly prevalent in children with an acute abdomen, and appendectomy is still the main method of treatment for this disease. The standard treatments for acute appendicitis are early open surgery and laparoscopic surgery. The aim: The aim of this study to show about comparison of single incision laparoscopic versus conventional laparoscopic appendectomy. Methods: By the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) 2020, this study was able to show that it met all of the requirements. This search approach, publications that came out between 2014 and 2024 were taken into account. Several different online reference sources, like Pubmed, SagePub, and Sciencedirect were used to do this. It was decided not to take into account review pieces, works that had already been published, or works that were only half done. Result: Eight publications were found to be directly related to our ongoing systematic examination after a rigorous three-level screening approach. Subsequently, a comprehensive analysis of the complete text was conducted, and additional scrutiny was given to these articles. Conclusion: HLA has a negative impact on quality of life and aesthetics because it requires three surgical incisions. On the contrary, in single-incision transumbilical laparoscopic appendicectomy (SILA), the incision is made around the umbilicus.

Reimaging of the Angami collective cultural identity: kenyü and customary law in the select Angami folktales

ABSTRACT Although various studies have focused on the formation of ethnicity in Nagaland, little is known about specific aspects of collective cultural identity derived from the folktales of the Angami tribe. There is a lack of research in understanding the cultural analysis of the forms of kenyü (an Angami expression representing a ‘proscription of behaviour’ 1 ) and its role in the wider social process, owing to the folktales as narratives in the representation of the ethnic identity of the Angami. Selecting four folktales from the Angami tribe provides a useful way of conceptualising the relationality of kenyü and the collective cultural identity. This paper undertakes a textual analysis of the selected folktales and applies Stuart Hall’s concept of ‘cultural identity’ and Anthony Smith’s idea of ‘ethno-symbolism’ to foreground the identification of the concept of kenyü in understanding the folktales to reimagine collective cultural identity as a key aspect of ethnic identity.

How Sensitive Are the Free AI-detector Tools in Detecting AI-generated Texts? A Comparison of Popular AI-detector Tools

Background: Recently, Artificial intelligence (AI) has significantly influenced academic writing. We aimed to investigate the sensitivity of the free versions of popular AI-detection software programs in detecting AI-generated text. Methods: We searched for AI-content-detection software on Google and selected the first 10 free versions that allowed a minimum of 500 words for text analysis. Then, we gave ChatGPT 3.5 version a command to generate a scientific article on the “Role of Electroconvulsive Therapy (ECT) in Treatment-resistant Depression” under 500 words. After generating the primary text, we rephrased it using three different software tools. We then used AI-detection software to analyse the original and paraphrase texts. Results: 10 AI-detector tools were tested on their ability to detect AI-generated text. The sensitivity ranged from 0% to 100%. 5 out of 10 tools detected AI-generated content with 100% accuracy. For paraphrased texts, Sapling and Undetectable AI detected all three software-generated contents with 100% accuracy. Meanwhile, Copyleaks, QuillBot, and Wordtune identified content generated by two software programs with 100% accuracy. Conclusion: The integration of AI technology in academic writing is becoming more prevalent. Nonetheless, relying solely on AI-generated content can diminish the author’s credibility, leading most academic journals to suggest limiting its use. AI-content-detection software programs have been developed to detect AI-generated or AI-assisted texts. Currently, some of the platforms are equally sensitive. However, future upgrades may enhance their ability to detect AI-generated text more accurately.

Exploring Linguistic Choices as a Representative of Eastern Culture: A Study of Moni Mohsin’s “The Diary of Social Butterfly”

Language and culture are entangled (Translations, 2018). A specific language typically points to a particular cluster of individuals. Language and culture share a symbiotic relationship. When people intermingle with people of different languages, it means that people are also intermingling with the values, norms and beliefs of that speaker. People cannot comprehend one's values without retrieving its language directly. When people learn a new language, it not only involves the learning of the structure of that language but also involves the learning about the cultural norms, values, manners and behavior. The main aim behind this research is to explore the linguistic choices as representative of Eastern culture in “The diary of Social Butterfly”. Textual analysis is performed in order to investigate the representation of culture and language in novel. This research has been conducted in the milieu of framework given by Sapir & Whorf and Wardhaugh (2011). The findings of the research reveal that Moni Mohsin has used food terminologies, kinship terminologies, dress terminologies, religious terminologies, professional terminologies and Festival terminologies of Eastern countries in order to highlight the Eastern culture. She has used words like Gulab Jamans Luddoos, shahi tukras, kheer, badaam ka halwa, Behari kebabs seekh kebabs, kaala, gora, bhai, ammi, saas, bahu, in sha Allah and many others. These all words are representatives of the culture of East.

Factor-Mimicking Portfolios for Climate Risk

We propose and implement a procedure to optimally hedge climate change risk. First, we construct climate risk indices through textual analysis of newspapers. Second, we present a new approach to compute factor-mimicking portfolios to build climate risk hedge portfolios. The new mimicking portfolio approach is much more efficient than traditional sorting or maximum correlation approaches by taking into account new methodologies of estimating large-dimensional covariance matrices in short samples. In an extensive empirical out-of-sample performance test, we demonstrate the superior all-around performance delivering markedly higher and statistically significant alphas and betas with the climate risk indices.

Research on China's End-of-Life Care Policy from the Perspective of Aging Population: A Textual Analysis of 30 Policies from 2017 to 2022

As the proportion of elderly population increases and the level of social development continues to rise, the issue of end-of-life care for the elderly has gradually gained societal attention. End-of-life care, as an emerging field, relies crucially on optimizing top-level policy design for its healthy development. This study focuses on 30 national-level end-of-life care policy texts from 2017 to 2022. Utilizing analysis tools such as ROST CM 6 software, NLPIR Chinese word segmentation system, and SPSS, the research employs a three-dimensional framework of keyword frequency analysis, semantic network analysis, and "policy tools-policy time-policy intensity" to comprehensively explore the current state of China's end-of-life care policy. The study reveals existing issues in the policy's practical operability, uneven application of policy tools, neglected funding and information technology support, and weak regulatory aspects. It emphasizes the need to prioritize a people-centered approach, enhance the overall balance in policy tools, promote the standardization of end-of-life care, and improve a diversified service system. These findings broaden the research perspective in the field of end-of-life care, providing insights for optimizing policy design and advancing nationwide end-of-life care efforts.

Bank sentiment and liquidity hoarding

AbstractWe analyze how bank sentiment affects bank liquidity hoarding, distinguishing unexplained beliefs of bank managers from fundamental‐based beliefs. We build a bank management sentiment measure from textual analysis of 10‐Ks and utilize a comprehensive bank liquidity hoarding measure. We find that negative bank sentiment increases liquidity hoarding not warranted by a bank's fundamental conditions or external circumstances. Further analysis confirms that our findings reflect bank volition rather than being driven solely by borrowers or depositors. We address endogeneity concerns using exogenous weather conditions as instruments. Overall, our findings suggest that bank sentiment can influence how much liquidity banks provide to the economy and financial system.

Jump volatility and firm‐specific investor sentiment

AbstractLiterature on investor sentiment has predominantly been conducted at the market level. Recent studies employing firm‐level sentiment have increasingly turned to textual analysis; however, the suitability of this type of proxy is still unverified. We utilize the Chinese stock market data from 2015 to 2023, aiming to discern whether the jump component of realized volatility possesses characteristics of investor sentiment. Our analysis reveals a pronounced short‐term persistence in jump volatility, particularly, among stocks that are hard to value and those with minimal institutional ownership. Further, we find that stocks exhibiting high monthly jump volatility consistently exhibit underperformance over extended periods, corroborating the hypothesis of sentiment‐induced temporary mispricing phenomena. Significantly, our findings advocate for the adoption of the jump component of realized volatility as a proxy for firm‐specific investor sentiment, offering a novel perspective in the sentiment analysis literature.

Social media marketing and customer purchase intention: Evidence-based bibliometrics and text analysis

The rapid proliferation of social media platforms has sparked heightened interest among businesses seeking to leverage them to enhance customer purchase intentions. Consequently, there has been a surge in research exploring the intersection of social media marketing and consumer behavior. However, gaps persist regarding the primary themes within this research domain. This study analyzes 282 research papers spanning from 2012 to 2022, sourced from the Web of Science Core Collection, focusing on social media and customer purchase intentions. Leveraging Latent Dirichlet Allocation (LDA) commands in STATA and VOSviewer software, the study investigates emerging trends and prevalent themes, visualizing the dataset. The findings indicate a notable increase in research output, particularly from developed countries, with significant collaboration between developed and developing nations. Moreover, the study identifies five principal research topics: 1) the impact of social media marketing on consumer purchase intention, 2) the consequences of online brand communities on purchase behavior, 3) factors influencing consumer purchase intention, 4) influencer effects on purchase intention, and 5) social media advertising and marketing strategies. Future inquiries should delve into various factors shaping customer purchase intentions, including the role of influencers, word-of-mouth dynamics, and advertising strategies while considering the diverse cultural contexts across different regions. This comprehensive analysis provides valuable insights for researchers and practitioners alike, guiding future endeavors in understanding and harnessing the power of social media in consumer decision-making processes. AcknowledgmentsGiang Hai Ha was funded by the Master, PhD Scholarship Programme of Vingroup Innovation Foundation (VINIF), code VINIF.2022.TS030.

SCREENING AND EARLY DETECTION OF LUNG CANCER: A COMPREHENSIVE SYSTEMATIC REVIEW

Background: Lung cancer is the second most commonly diagnosed cancer and the leading cause of cancer-related deaths globally, accounting for the greatest economic and public health burden of all cancers. In 2020, lung cancer accounted for approximately 2.2 million cases and nearly 1.8 million deaths worldwide. The aim: The aim of this study to show about screening and early detection of lung cancer. Methods: By the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) 2020, this study was able to show that it met all of the requirements. This search approach, publications that came out between 2014 and 2024 were taken into account. Several different online reference sources, like Pubmed, SagePub, and Sciencedirect were used to do this. It was decided not to take into account review pieces, works that had already been published, or works that were only half done. Result: Four publications were found to be directly related to our ongoing systematic examination after a rigorous three-level screening approach. Subsequently, a comprehensive analysis of the complete text was conducted, and additional scrutiny was given to these articles. Conclusion: Early screening and diagnostic methods of lung cancer, x-ray screening is not recommended. LDCT has obvious advantages and is the most promising imaging method in early screening of lung cancer.

EXPRESS: Gender and Serious Drug Recalls: a Textual Sentiment Analysis of Drug Reviews on WebMD

Consumers taking prescription drugs have limited ability to ascertain drug quality before taking the drug. After drug use, however, consumers frequently report their personal experiences with prescription drugs on one of the world’s largest medical websites: WebMD. Drug reviews on WebMD are a potentially rich source of free-form text that can be utilized to inform firms, consumers, researchers, and the Food and Drug Administration (FDA) about the quality and safety of prescription drugs. Additionally, because men and women communicate in starkly different ways, the gender of the reviewer may play a key role in drug reviews signaling drug quality problems. We examine if drug review textual sentiment is associated with the hazard of a serious drug recall and whether this relationship varies depending on the gender of the reviewer. We analyze textual sentiment on drug reviews from WebMD along with 13 years of drug recall data using several hazard models. We find that the more negative the drug review sentiment, the greater the hazard of a serious recall on that drug. This relationship is completely explained by drug reviews written by females; reviews written by males have no explanatory power. Our findings are confirmed by numerous robustness checks. In post-hoc analysis, we explore possible mechanisms by comparing female and male adverse events on the recalled drugs in our study. Our contributions to gender diversity and drug quality literature leads to implications for the FDA, WebMD, and firms that manufacture prescription drugs.

Navigating Power Structures: Symbolism, Realism, and Naturalism in The Grapes of Wrath through a Postcolonial Lens

This paper explores the representation and negotiation of power systems in John Steinbeck’s famous book “The Grapes of Wrath” by using a postcolonial framework. This study seeks to identify the manner in which questions of power, oppression, and resistance are depicted in the book by analyzing its themes of symbolism, realism, and naturalism through the lens of postcolonial theory. This study examines the symbolic meaning of people, situations, and events connected to hegemonic systems and colonial legacies through rigorous textual analysis. Additionally, it explores how the novel’s naturalism and realism illuminate the historical, socio-economic and environmental surroundings, emphasizing the connection between systemic inequality and power dynamics. This study clarifies how colonial ideas sustain exploitation and disenfranchisement by examining the experiences of marginalized groups, including tenant farmers, migrant labourers, and indigenous communities. Finally, this study advances our knowledge of how literature can be a platform for opposing and criticizing established power systems. It provides insights into the resilience and resistance strategies used by marginalized people.

Economies of Inequality? Polycentric Metropolitan Governance and Strategic Sustainability Choices

This article examines the relationship between the political fragmentation of cities in metropolitan regions, the distribution of social vulnerability, and the city-level economic and social sustainability strategies they adopt. Strategies emerge from prevailing community norms, and polycentric governance arrangements can support conditions in which both economic and social sustainability strategies emerge as compliments, contrary to the concern that fragmentation spurs zero-sum competition. Combining surveys of U.S. cities with social vulnerability data and text analysis of planning documents, we find that greater fragmentation has a negative impact on the sustainable development strategies cities adopt. However, growth and sustainable development strategies tend to develop alongside social sustainability efforts to address human needs. We conclude that development strategies emerge in polycentric systems in relation to the degree of fragmentation which exists, and that subsequent work should continue to focus on identifying these entropic thresholds in order to effectively address lingering inequities.

Fail or pass? Investigating learning experiences and interactive roles in MOOC discussion board

In massive open online course (MOOC) discussion board, students' learning experience, reflecting implicit cognitive and affective states, is related to their learning outcomes and course's completion rates. The majority of researches about learning experience identification in MOOCs depend on post-hoc questionnaires, which may encounter issues such as personal biases, hazy memories, or time constraints, and distribution difficulty in MOOCs. Moreover, learning experience is influenced by students' interactions during learning but their relationship has not been thoroughly explored. This study aimed to address these issues. Firstly, it proposed an artificial intelligence-based text analysis approach for automatically identifying patterns of learning experiences from the large-scale students' posts in MOOC discussion board. It had performance advantage in terms of accuracy when compared with the other competing approaches. Secondly, this study defined students' interactive roles from both social relations and interaction behaviors in MOOC discussion board, and analyzed learning experiences corresponding to the different interactive roles. For students with high participation and low influence in interactions, flow and boredom were prone to happen, while for students with low participation and high influence in interactions, anxiety and apathy were easy to generate. Finally, this study revealed the effect of learning experience on learning achievement with respect to interactive role. For students with high participation characteristics, their learning achievements were less affected by learning experience, while for students less active in interaction, flow was related with good learning achievements. In summary, this study had significant methodological implications for automated learning experience identification. Moreover, this study revealed importance of interactive role in describing the interplay between learning experience and learning achievement, and provided suggestions for the improvement of MOOCs.

Analysis and Prevention of AI-Based Phishing Email Attacks

Phishing email attacks are among the most common and most harmful cybersecurity attacks. With the emergence of generative AI, phishing attacks can be based on emails generated automatically, making it more difficult to detect them. That is, instead of a single email format sent to a large number of recipients, generative AI can be used to send each potential victim a different email, making it more difficult for cybersecurity systems to identify the scam email before it reaches the recipient. Here, we describe a corpus of AI-generated phishing emails. We also use different machine learning tools to test the ability of automatic text analysis to identify AI-generated phishing emails. The results are encouraging, and show that machine learning tools can identify an AI-generated phishing email with high accuracy compared to regular emails or human-generated scam emails. By applying descriptive analytics, the specific differences between AI-generated emails and manually crafted scam emails are profiled and show that AI-generated emails are different in their style from human-generated phishing email scams. Therefore, automatic identification tools can be used as a warning for the user. The paper also describes the corpus of AI-generated phishing emails that are made open to the public and can be used for consequent studies. While the ability of machine learning to detect AI-generated phishing emails is encouraging, AI-generated phishing emails are different from regular phishing emails, and therefore, it is important to train machine learning systems also with AI-generated emails in order to repel future phishing attacks that are powered by generative AI.

Developing a smart green supplier risk assessment system integrating natural language processing and life cycle assessment based on AHP framework: An empirical study

Global carbon reduction drives the transformations of corporations, emphasizing carbon and environmental impact within supply chains. A critical challenge in risk management is converting unstructured data into quantifiable information, and ruining the conversion often leads to ineffective risk assessments. While artificial intelligence is increasingly used in supply chain risk management, previous studies seldom integrate text analysis for risk extraction and lack accurate risk assessment methods. This study pioneers an intelligent green supplier risk assessment system integrating natural language processing (NLP) and life cycle assessment (LCA) based on an analytic hierarchy process (AHP) framework. The proposed approach utilizes NLP keyword extraction to identify and assess risk and uses LCA to uncover environmental risks, minimizing negative impacts. The text classification model attains 81.7 % accuracy, ensuring a trustworthy risk assessment system. The proposed method could significantly improve risk analysis efficiency, foster sustainable procurement, and elevate enterprise competitiveness in sustainable business practices.

ТЕКСТОВЫЙ АНАЛИЗ ПРЕДПРИНИМАТЕЛЬСКОЙ ОРИЕНТАЦИИ: ТЕОРИЯ И ПРАКТИКА

Entrepreneurial Orientation (EO) is a key theme in the field of entrepreneurial research, having a profound impact on the development and success of businesses. This paper utilizes a textual analysis approach to comprehensively review the literature on EO, examining the concept from three aspects: the conceptualization of EO, the construction of measurement scales, and empirical research findings. We find that there is debate within the academic community regarding the definition and dimensional structure of EO, the construction and choice of measurement scales, and the mechanisms and moderating factors linking EO to business performance, with no comprehensive consensus achieved. This lack of consensus provides a rich field of options for future theoretical and empirical research on EO. Future studies should focus on achieving theoretical consistency and establishing a dominant academic discourse, while also recommending the integration of alternative measurement tools and improved analytical methods to expand the scope and depth of empirical research. This will enrich the development of EO theory and its application across various economic and social domains.

Affecting the future: A multi-method qualitative text and discourse analysis of emotions in Australian news reporting on climate change and climate anxiety

Eco-anxiety and associated emotions are on the rise. International estimates range from 25–68% prevalence. Australians now regard climate change as their top concern for the future, with some young people reconsidering their intentions to become parents. The emotional sequela from climate change is becoming clearer. How it is conceptualised, responded to, and reinforced within public discourse requires further consideration. This paper presents a multi-method qualitative text and discourse analysis of Australian online news articles published in 2022 reporting on emotions and our ecological future. Drawing on sociological theories of emotions and Foucauldian conceptualisations of discourse, we present insights into the potency of emotions and discourses within online news media. We identify four differing conceptualisations of emotions, interpret what these discourses can do, and conclude with ways in which the public can reclaim agency in resisting discourses that engender passivity in the context of future ecological threats.