Text Analysis Techniques Research Articles

Comparing clubs: Analyzing ambitions in the G7 and the G20

Mini-lateral ‘clubs’ occupy an increasingly prominent place in the international environmental governance landscape. Yet few studies have looked at how differences between clubs influence the results they produce. This paper aims to fill this gap in understanding by testing hypotheses on how different clubs' membership constellations and leadership (connected to large events) affect ambitions in outcome documents of the G7 and the G20. It tests those hypotheses by employing text and data analytic techniques to compare stated ambitions in environmental documents of G7 and G20 over the past two decades. The analysis reveals that the G7’s language is generally stronger than the G20; and that strategic leadership connected to large events may contribute to raising those ambitions. These findings highlight the importance of mini-lateral clubs as forms of environmental governance and, more generally, illustrates the use of text mining in environmental governance research.

Konstruksi Sosial dan Politik dalam Perkembangan Pendidikan Islam

Social and political life has a significant influence on the development of Islamic education, thus requiring in-depth study to find its development construction in the national education map. For this reason, this article will focus its study on how social and political systems affect the development of Islamic education by examining the construction of social and political systems. This research uses a qualitative approach to library research to explore, examine, and identify study topics in the literature. Both primary and secondary data sources are analyzed using text analysis techniques by reading literature data, identifying, and classifying data according to discussion, then discussing and presenting to obtain conclusions based on the focus of the study. The results oh the study show among others1) the political map of education policy in Indonesia provides direction for the development of Islamic education with the development of curriculum substance; 2) social and political systems have a reciprocal impact on the development of Islamic education. On the one hand, the social and political system has a significant impact on education, on the other hand, education shapes the social and political system; 3) the reorientation of Islamic education can balance the lag by answering the challenges of the times, covering the weaknesses of Islamic education, and returning Islamic education to its functional basis

Does cybersecurity risk stifle corporate innovation activities?

Cybersecurity risk has become a major concern for organizations due to its potential impact on a variety of corporate activities. This paper examines the impact of cybersecurity risk on corporate innovation activities and uncovers two important channels: risk-taking and precautionary savings. Employing textual analysis and machine learning techniques to estimate firms' ex-ante cybersecurity risk for a sample of U.S. listed firms, we show that cybersecurity risk is negatively related to corporate innovation. We address potential endogeneity biases and find the results to remain unchanged. Furthermore, our results are robust to alternative proxies, truncation issues, and external cybersecurity risk. We uncover the mechanisms underlying the main result by showing that the effects are more pronounced for firms with lower tolerance to risk and lower cash savings. Innovations of smaller, financially constrained firms and firms belonging to high cybersecurity risk and technology-intensive industries are affected more.

Topic Modeling based Text Classification Regarding Islamophobia using Word Embedding and Transformers Techniques

Islamophobia is a rising area of concern in the current era where Muslims face discrimination and receive negative perspectives towards their religion, Islam. Islamophobia is a type of racism that is being practiced by individuals, groups, and organizations worldwide. Moreover, the ease of access to social media platforms and their augmented usage has also contributed to spreading hate speech, false information, and negative opinions about Islam. In this research study, we focused to detect Islamophobic textual content shared on various social media platforms. We explored the state-of-the-art techniques being followed in text data mining and Natural Language Processing (NLP). Topic modelling algorithm Latent Dirichlet Allocation is used to find top topics. Then, word embedding approaches such as Word2Vec and Global Vectors for word representation (GloVe) are used as feature extraction techniques. For text classification, we utilized modern text analysis techniques of transformers-based Deep Learning algorithms named Bidirectional Encoders Representation from Transformers (BERT) and Generative Pre-Trained Transformer (GPT). For results comparison, we conducted an extensive empirical analysis of Machine Learning algorithms and Deep Learning using conventional textual features such as the Term Frequency-Inverse Document Frequency, N-gram, and Bag of words (BoW). The empirical based results evaluated using standard performance evaluation measures show that the proposed approach effectively detects the textual content related to Islamophobia. In the corpus of the study under Machine Learning models Support Vector Machine (SVM) performed best with an F1 score of 91%. The Transformer based core NLP models and the Deep Learning model Convolutional Neural Network (CNN) when combined with GloVe performed best among all the techniques except SVM with BoW. GPT, SVM when combined with BoW and BERT yielded the best F1 score of 92%, 92% and 91.9% respectively, while CNN performed slightly poor with an F1 score of 91%.

The Gender Gap in Issue Attention and Language Use within a Legislative Setting: An Application to the Italian Parliament (1948–2020)

Abstract We investigate the gender gap in issue attention among members of parliament (MPs) by applying automated text analytic techniques to a novel data set on Italian parliamentary speeches over a remarkably long period (1948–2020). We detect a gendered specialization across issues that tends to disappear as women’s shares in parliamentary groups increase. We then investigate whether women’s access to previously male-owned issues brings with it a different agenda, operationalized as a different vocabulary. We detect a U-shaped pattern: language gender specificity is high when female MPs are tokens in parliamentary groups with a large preponderance of men; it decreases when their shares start increasing and grows again when they constitute a considerable minority. We argue that this pattern is consistent with the theory of tokenism, and it is produced by the interlinkage of commitment to shared norms and the distribution of “activation thresholds” among female MPs.

Acquisition of Agricultural Land by Domestic and Foreign Legal Entities: Legal Prospects for Ukraine and other Countries

The aim of the research was to assess the legal framework for the acquisition of agricultural land by domestic and foreign legal entities, using the rules and regulations on the agricultural land market in Ukraine as an example of a system with ill-founded restrictions in this area. To accomplish this task, the authors resort to a set of scientific methods, including comparative review, systematic review and standard techniques of text analysis. The main result of the research was that it is imperative for Ukraine, taking into account that European integration is a key and unalterable priority of its foreign policy, to grant a general permission for foreign natural and legal persons to acquire agricultural land, as well as to introduce flexible approaches to setting acquisition limits. It is concluded that, the attention of policy makers should also focus on the need to deploy legal and institutional mechanisms that can respond to the challenges and risks associated with a significant degree of freedom of movement of agricultural land. This could include establishing in contracts for the alienation of agricultural land the obligations of buyers in relation to its rational use.

Interpretation of tax law in cases involving commercial entities: Opportunities to exchange best practices in the area of corporate social responsibility regulation

The article aims to develop a correct understanding of the essence and implications of the basic principles and legal provisions governing tax matters, as well as to form an insight into their evolutionary transformations on the basis of the exchange of relevant best practices between Ukraine and other countries. Relying on methods of comparative review, as well as methods of systematic review and standard techniques of text analysis, the author covers theoretical and practical issues related to the balanced combination of literal and intentional interpretation of tax legislation provisions, in dubio pro tributario in the interpretation of tax laws and question of reasonable cause and good faith of taxpayers. It is noted, in particular, that common law countries and continental legal systems are united by a tendency towards a balanced combination of literal and purposive interpretation. It is emphasized in the conclusions that, along with the literal wording of tax law provisions, the purpose of their introduction and the general principles of tax law are taken into account. Moreover, in some countries, reference to the intention of the legislators is even allowed.

Artificial Intelligence and Wastewater Treatment: A Global Scientific Perspective through Text Mining

The concept of using wastewater as a substitute for limited water resources and environmental protection has enabled this sector to make major technological advancements and, as a result, has given us an abundance of physical data, including chemical, biological, and microbiological information. It is easier to comprehend wastewater treatment systems after studying this data. In order to achieve this, a number of studies use machine learning (ML) algorithms as a proactive approach to solving issues and modeling the functionalities of these processing systems while utilizing the experimental data gathered. The goal of this article is to use textual analysis techniques to extract the most popular machine learning models from scientific documents in the “Web of Science” database and analyze their relevance and historical development. This will help provide a general overview and global scientific follow-up of publications dealing with the application of artificial intelligence (AI) to overcome the challenges faced in wastewater treatment technologies. The findings suggest that developed countries are the major publishers of articles on this research topic, and an analysis of the publication trend reveals an exponential rise in numbers, reflecting the scientific community’s interest in the subject. As well, the results indicate that supervised learning is popular among researchers, with the Artificial Neural Network (ANN), Random Forest (RF), Support Vector Machine (SVM), Linear Regression (LR), Adaptive Neuro-Fuzzy Inference System (ANFIS), Decision Tree (DT), and Gradient Boosting (GB) being the machine learning models most frequently employed in the wastewater treatment domain. Research on optimization methods reveals that the most well-known method for calibrating models is genetic algorithms (GA). Finally, machine learning benefits wastewater treatment by enhancing data analysis accuracy and efficiency. Yet challenges arise as model training demands ample, high-quality data. Moreover, the limited interpretability of machine learning models complicates comprehension of the underlying mechanisms and decisions in wastewater treatment.

Is voluntary risk disclosure informative? The role of UK firm-level governance

PurposeThe study investigates how firm-level governance (FL_G) affects the disclosure of voluntary risk information. Likewise, it explores the influence of FL_G on the informativeness of voluntary risk disclosure (VRD). Specifically, it examines how FL_G shapes the nexus between VRD and firm value.Design/methodology/approachIt uses a sample of non-financial firms from the FTSE350 index listed on the London Stock Exchange between 2010 and 2018. The authors utilise an automated textual analysis technique to code the VRD in the annual reports of these firms. The firm value, adjusted for the industry median, is a proxy for investor response to VRD.FindingsThe results suggest that UK firms with significant board independence and larger audit committees disclose more risk information voluntarily. Nevertheless, firms with larger boards of directors and higher managerial ownership disseminate less voluntary risk information. Besides, VRD contains relevant information that enhances investors' valuation of UK firms. These results are more pronounced in firms with higher independent directors, lower managerial ownership and large audit committees.Practical implicationsThe study rationalises the ongoing debate on the effect of FL_G on VRD. The findings are helpful to UK policy-setters in reconsidering the guidelines that regulate UK VRD and to the UK investors in considering risk disclosure in their price decisions and thus enhancing their corporate valuations.Originality/valueIt contributes to the risk reporting literature in the UK by presenting the first evidence on the effect of a comprehensive set of FL_G on VRD. Besides, it enriches the existing research by shedding light on the role of FL_G on the informativeness of discretionary risk information in the UK.

More than Meets the Eye? Using Text Analytic Techniques to Unpack School Mission Statements

Schools develop mission statements in part to communicate their purposes of schooling to internal and external audiences. The goal of this study is to employ text analytic techniques to analyze school mission statements. Focusing on Arizona and New Jersey’s schools, we seek to understand: 1) what themes (topics) emerge from their mission statements, 2) whether local context (politics) and institutional factors (being a charter) mediate topic prevalence, and 3) how similar school mission statements are to one another overall and across select factors. Using structural topic modeling we find that five topics emerge as particularly prevalent, and they address key purposes within the US context related to social, academic, and civic development with an emphasis on a safe environment and a sense of community. Local political leanings have a minor impact on the prevalence of topics but being a charter has a distinct influence. Compared to regular schools, charters are more likely to include themes related to preparing for college, academic approaches, and character and family ties, but they place lower emphasis on community and citizenship themes. School missions display moderate levels of similarity, indicating that a common set vocabulary has permeated schools’ missions, though differences remain, including between states. Overall, this study deepens our understanding of the varieties of schools’ missions and reveals text analytic techniques are well suited for uncovering them.

Confession and greenwashing: the impact of water information disclosure on firm value

Water pollution has become a serious problem in recent years, and firms are one of the main culprits for this environmental issue. Encouraging companies to improve water management behavior is necessary to protect water resources. Based on panel data of Chinese A-share listed companies in water-sensitive industries, this study used text analysis techniques to study the impact of corporate water information disclosure on pollutant emissions, strategy on firm value, and the U-shaped moderating role of local governments’ environmental regulation. The results show that (1) an increase in the amount of emission information texts to confess the water status can help enhance firm value. (2) The increase in the amount of strategic information texts, both the tone of emission, and strategic information texts have negative impacts on firm value, which help enterprises greenwash. Further analyses find a U-shaped moderating effect of governments’ environmental regulation on the relationships between emission information disclosure, strategic information disclosure and firm value, and varies under the different ISO14001 certification situations and life cycles. This research explains the effectiveness of corporate water information disclosure and the influence of governments’ environmental regulation, which plays a vital role in promoting firms to improve their environmental behaviors, reduce water pollution, and further achieve green development.

Microdosing psychedelics: The segregation of spiritual and scientific narratives within the r/microdosing online community

AbstractBackground and aimsMicrodosing psychedelics refers to the practice of repeatedly ingesting doses that do not reach the threshold for perceptual alterations. This practice has gained attention from mass media, businesses, and the general public, as evidenced by the proliferation of online communities dedicated to it. In this contribution, we examine the content generated within the online community r/microdosing from its creation on October 16, 2013, until the day of data collection on October 31, 2020. Our aim is to examine the narratives reflected by users' contributions, specifically the compatibility or incompatibility of spiritual and scientific narratives.MethodsIn this contribution, we used text analysis techniques and examined the content generated within the online community r/microdosing from its creation on October 16, 2013, until the day of data collection on October 31, 2020.ResultsWe clearly identified a topic that reflects a spirituality narrative as well as a topic that we coined as “neuro-cognition” and that reflects a scientific narrative. These topics were typically not present within the contributions of the same users, suggesting that the scientific and spiritual narratives are segregated within the r/subreddit community.ConclusionOur approach emphasizes the potential of text analytic techniques for uncovering the cultural repertoire surrounding a particular practice, in our case, the practice of microdosing psychedelics.

Text-Based Measure of Supply Chain Risk Exposure

Using textual analysis techniques, including seeded word embedding and bag-of-words-based content analysis, I develop a firm-level measure of supply chain risk exposure from a novel source of unstructured data—the discussion between managers and equity analysts on supply chain-related topics during firms’ quarterly earnings conference calls. I validate the measure by showing that (1) the measure exhibits intuitive variations over time and across firms, successfully capturing both routine and systematic supply chain risk events; and (2) the measure is about risk exposure, as it significantly correlates with realized and options-implied stock return volatility, even after controlling for well-known aggregate risk measures. I then demonstrate that the measure is specifically indicative of the supply chain component of risk exposure. (3) Consistent with theoretical predictions, firms facing higher supply chain risks have higher inventory buffers, particularly in raw materials and intermediate inputs, increased cash holdings in lieu of investments, and significantly lower trade credit received from suppliers. Moreover, (4) during unexpected risk episodes, such as the Tohoku earthquake, firms with higher ex ante risk exposure have worse operating and financial performance. These results indicate that the text-based measure provides a credible quantification of firm-level exposure to supply chain risks and can thus be reliably utilized as outcome or explanatory variables in empirical supply chain research. This paper was accepted by Jeannette Song, operations management. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4927 .

Textual Emotion Analysis-based Disabled People Talking Using Improved Metaheuristics with Deep Learning Techniques for Intelligent Systems

Due to the complexity of generalizing and modeling the series of brain signals, detecting emotions in people with sensory disabilities still continues to be challenging. Hence, brain–computer interface technology was used to study the emotions and behavior of people based on brain signals. Emotion analysis is a widely used and robust data mining analysis method. It provides an excellent opportunity to monitor, evaluate, determine, and understand the sentiments of consumers with respect to a product or a service. Yet, a recognition model of emotions in people with visual disabilities has not been evaluated, even though previous studies have already proposed the classification of emotions in people with sensory disabilities using machine learning approaches. Therefore, this study introduces a new salp swarm algorithm with deep recurrent neural network-based textual emotion analysis (SSADRNN-TEA) technique for disabled persons. The major intention of the SSADRNN-TEA technique was to focus on the detection and classification of emotions that exist in social media content. In this work, the SSADRNN-TEA technique undergoes preprocessing to make the input data compatible with the latter stages of processing and BERT word embedding process is applied. Moreover, deep recurrent neural network (DRNN) model is exploited. Finally, SSA is exploited for the optimal adjustment of the DRNN hyperparameters. A widespread experiment is involved in simulating the real-time performance of the SSADRNN-TEA method. The experimental values revealed the improved performance of the SSADRNN-TEA technique in terms of several evaluation metrics.

Kajian Puisi-Puisi Pernyataan Rindu Karya M. Hanfanaraya Menggunakan Pendekatan Semiotika

Semiotics is a study of signs. The poems of Pengagum Rindu by M. Hanfanaraya contains elements of semiotics such as icons, indexes, and symbols. The purpose of the study was to identify and analyze semiotics in the poems of Pengagum Rindu by M. Hanfanaraya. The scope of the research is the study of literary criticism, namely the study of semiotics. The limitation of the problem in this research is that the author takes all aspects of semiotics on the types of signs such as icons, indexes, and symbols. There are two sources of data, namely primary data sources and secondary data sources. This type of research is a qualitative research using a descriptive qualitative approach. Data collection techniques used are hermeneutic and documentation techniques. The data analysis technique uses text analysis techniques. The results of the research that were found were (9) the symbol aspect was found as many as 1(one) data consisting of words, combinations of words, and phrases.
 

Qualifying the Quantified: Structural Topic Modeling Analysis of Engagement in Digital Health Platform for Dementia Caregivers

Qualitative analysis methods, while crucial for understanding complex factors influencing human behaviors like engagement with digital health technologies, can be conceptually challenging, time-consuming, and resource intensive. To address these challenges, semi-automated text analysis techniques like structural topic modeling (STM) may enhance the efficiency of qualitative analysis. This study investigates how STM can facilitate qualitative data analysis to gain insights into engagement with CareVirtue, a web-based health platform for dementia caregivers. We employed STM on interview data, using the number of CareVirtue journal posts as a covariate to represent caregiver engagement. Our STM model revealed six topics with varying levels of association with engagement. The topics of “recalling positive experiences” and “help from a care network” were associated with high engagement. These topics complement qualitative analysis by providing a deeper understanding of specific topics and demonstrate the potential of quantitative methods, such as STM, to support and augment qualitative analysis.

Customs binding information decisions according to the law of Canada: peculiarities and lessons for European countries

The purpose of this research is to determine the peculiarities of the legal framework for scope of subject matter and rules for issuing, modification or revocation of customs advance rulings (customs binding information decisions) from the point of view of prospects of their implementation by European countries to further improve the effectiveness of this mean of customs administration within their jurisdictions. The methodological basis of the study comprises of comparative review methods as well as systematic review methods and standard techniques of text analysis with their due adjustment to legislative material. Results: the author studied Canadian legislation making provision for the scope of matters for national customs ruling (customs binding information decisions), the grounds and legal consequences of their modification and revocation or cancellation, including their ultra-active use through postponement of the effective date of the modification or revocation, as well as the procedure for publishing of national customs rulings for ensuring the uniformity of the conclusions of customs authorities expressed in them. The particular attention is attached to those rules and regulations that could serve as a comparative legal basis for the improvement of parts of customs legislation of European countries, which concern customs binding information decisions. Conclusions: in light of the purpose of this research of particular interest are the Canadian legislative solutions concerning: 1) establishing the need for the applicant to indicate in his application for the issuance of a national customs ruling, whether to the best of their knowledge the respective issue was the subject of another/separate request for a national customs ruling, administrative or judicial appeal, which are as grounds for suspending (postponing) consideration of the request for the issuance of a national customs ruling; 2) the grounds for the occurrence of retrospective legal consequences of the modification or revocation of a national customs ruling in relation to goods imported into the customs territory before its modification or revocation; 3) determination for the purposes of ultra-active use (postponement of the effective date of the modification or revocation) of the national customs ruling, which exactly is considered to be the evidence of reliance on the national customs ruling in good faith; 4) formation of a publicly available online repository of national customs rulings to promote the uniformity and transparency of customs administration, as well as the introduction of information and telecommunication tools for submission of requests for national customs rulings, their further implementation, as well as for notification of interested parties regarding changes in their status and other issues, relating to the circulation of national customs rulings.

Exploring the Role of Libraries in Promoting Child Mental Health in Bangladesh: A Study on Some Selected Libraries

Aims: The research aimed to figure out the existing roles of libraries in promoting child mental health. The study also focused on the child's mental health importance, the warning sign of children, common disorders and promotional strategies for child mental health.
 Methodology: To figure out these roles’ the researcher adopted qualitative research. For this study, the researcher collected data by a scheduled interview, the respondents were chosen mostly from the public libraries and one from Shishu academy library. In line, the text analysis technique was used to identify the different types of roles.
 Results: The study's key findings are presented from three perspectives: firstly, the socio-economic determinants of child mental health. Secondly, libraries' role as services providers, as bibliotherapists and as motivators which affects children’s mental health, and develops their thinking capability. Finally, libraries can flourish in their role by adequate books, health equipment, and by collaborating with the school library to organize workshop.
 Conclusion: The study's conclusion is to draw the attention of the important stakeholders to the significance of children's mental health and the librarian's role in encouraging it through specialized read-aloud programs, helpful resources, and a welcoming library environment. Stakeholders should take proactive measures to promote and fund these programs by acknowledging the important effects that early exposure to literature and positive reading experiences can have a great impact on a child's mental well-being. This will help to establish a nurturing and enriching environment.

A comparative study of the characteristics of hate speech propagators and their behaviours over Twitter social media platform

The internet and social media have facilitated diverse communication genres, enabling widespread and rapid opinions-sharing. However, hate speech imposes a contemporary challenge on individuals and communities, given the user anonymity, freedom, and inadequate regulation. Therefore, it is imperative to identify the perpetrators responsible for spreading hate content and examine their behaviour to prevent and mitigate the negative impact. This study aimed to compare the characteristics of hate speech propagators and their behaviour with non-hate users on Twitter for the first time in Sri Lanka. The intrinsic and extrinsic profile features were extensively analyzed, employing Sinhala and English text analysis techniques. A corpus of 102882 posts from 530 hate and non-hate Twitter user profiles was selected for the study. This study investigates the unique characteristics of hate speech propagators and non-hate users by examining their profile self-presentation, conducting social network analysis, and analyzing sentiment and emotion through linguistic analysis. Hate users often refrained from expression, with infrequent account verification and geotagging. They tend to have a higher follower and following counts and more favourites, group memberships, and statuses than non-hate users. However, general Twitter user engagement with hate users was significantly low, with fewer likes, retweets, and replies. The limited involvement of normal users with hate content indicates that audiences can be effectively utilized to combat hate speech. The sentiment analysis between languages showed polarisation of negative tweets towards Sinhala, with the synergistic effect of English language users using positive sentiment to spread hate content. The novel findings shed light on the characteristics of hate users, facilitating their early detection and moderation of hate speech and aiding in developing algorithms to rank and categorize hate users using artificial intelligence. Moreover, it can be used for policy reforms, awareness programmes, and building social cohesion while combating hate speech.

PEMIKIRAN PRAGMATISME IBNU KHALDUN DAN RELEVANSINYA DENGAN MERDEKA BELAJAR KURIKULUM MERDEKA

Link and match as posterity educational project. This project aims to connect the knowledge in schools with the citizen needs. In Islamic literature mentioned that Ibn Khaldun is an influential Muslim figure. The Muqaddimah book which written became a media for his brilliant ideas in the society social order, including educational practices. Through a literature review of Ibn Khaldun's thoughts used in books and journal articles using text and context analysis techniques, it can be interpreted that Ibn Khaldun's pragmatism-instrumental thinking has relevance to independent learning in the independent curriculum (MBKM) in Indonesia. The mean of relevance in the al-Hiwar method to realize students get additional insight of knowledge through the integration of subject matter and theory obtained in class with practical experience outside the classroom and the surrounding community.