Online Text Research Articles

Identification of Tampering in Arabic Text Documents Using Zero-Watermarking Algorithm

The internet makes sharing information easy, but protecting copyrights and verifying the authentication of online text remains a challenge. Current methods for securing Arabic text are limited. This research introduces a new tool: a zero watermark algorithm designed specifically for Arabic text. This new algorithm protects Arabic text by analyzing its content. It creates a watermark based on a chosen keyword (at least 6 characters, no duplicates), and how often each character appears in different forms (separate, connected), and positions (beginning, middle, and end) within the text. The proposed method was tested on nine different Arabic text samples of varying size, simulating various tampering attempts like inserting, deleting, and rephrasing text. The results are impressive, showing that the algorithm outperforms existing methods in detecting even minor changes.

Communicating blood test results in primary care: a mixed methods systematic review.

Background Test result communication is important for patient-centred care, patient safety and primary care workload. Evidence is needed to ensure that test results are communicated safely and efficiently to patients in primary care. Aim To summarize existing evidence for blood test result communication between primary care providers and their patients and carers. Design and setting Mixed-methods systematic review Methods Medline, Embase, PsycINFO (Ovid); CINAHL (ESCOHost); and the Cochrane Library were searched from 2013 to September 2023. Primary studies of any design that provided information on the communication of blood test results by primary care staff to adult patients and carers were eligible for inclusion. Results There were 71 included studies, including 10 experimental studies and no randomized controlled trials. Study quality was mostly poor and risk of bias was high, partly due to a lack of reported information. Patients want more information about their blood test results, particularly in terms of 'what next', and prefer results to be provided quickly. Electronic methods such as online access or text messages were generally well accepted but not by everyone, and not for all results. Clinicians' opinions were mixed as to whether more information and direct release of test results to patients without clinician input was beneficial or could cause problems, such as increased workload. Conclusions We have identified a range of evidence on patient and clinician preferences, barriers and facilitators to test communication, which is particularly important in the current NHS context of a move towards patient online access.

‘Tortured phrases’ impact the integrity of the environmental literature

In environmental science, it is necessary to accurately describe processes, methods and phenomena using established technical terms and jargon. Any significant deviation from such terms might leave readers and peers confused, while confusion can lead to misinterpretations, opening up the possibility of errors. During peer review and prior to publication in a peer-reviewed environmental journal, it is thus incumbent upon editors and peer reviewers, and to a lesser extent copy editors, to verify that terminology in a scientific paper is accurate. In this brief communication, 61 papers with cases of ‘tortured phrases’, which are terms that have – for some reason – come to replace established jargon, are described in indexed environmental literature, frequently in indexed journals that are generally associated with reputable publishers. Of the 61 papers, 13 have been retracted, suggesting an erosion of the papers’ integrity. Awareness of this phenomenon and these cases allows editors and peer reviewers of environmental journals to be more careful when screening and vetting submitted papers, but should also serve as a lesson for authors to be more careful when writing their papers, avoiding the temptation to automatically incorporate text that online text thesauruses may provide, or to use non-standard terms.

Grammatical Alliance in the Acehian Language

This research aims to describe the grammatical alliance system found in the Acehnese language. The research method used in this research is descriptive-qualitative. Miles and Huberman Model Qualitative Data Analysis Techniques Miles and Huberman can be carried out in three stages, namely data reduction, data display, and conclusion drawing and verification. Data was collected through online or offline searches, including from digital text databases and online sources, in Acehnese, namely Acehnese song lyrics. Comparison with relevant literature was also used to ensure the consistency and validity of the findings. Based on this, 16 lines were found in two Aceh-language regional songs. The data found that the Acehnese language belongs to the accusative type, which treats S the same as A and gives a gives a different treatment to P (S = A ≠ P).

Automatic detection of problem-gambling signs from online texts using large language models.

Problem gambling is a major public health concern and is associated with profound psychological distress and economic problems. There are numerous gambling communities on the internet where users exchange information about games, gambling tactics, as well as gambling-related problems. Individuals exhibiting higher levels of problem gambling engage more in such communities. Online gambling communities may provide insights into problem-gambling behaviour. Using data scraped from a major German gambling discussion board, we fine-tuned a large language model, specifically a Bidirectional Encoder Representations from Transformers (BERT) model, to predict signs of problem-gambling from forum posts. Training data were generated by manual annotation and by taking into account diagnostic criteria and gambling-related cognitive distortions. Using cross-validation, our models achieved a precision of 0.95 and F1 score of 0.71, demonstrating that satisfactory classification performance can be achieved by generating high-quality training material through manual annotation based on diagnostic criteria. The current study confirms that a BERT-based model can be reliably used on small data sets and to detect signatures of problem gambling in online communication data. Such computational approaches may have potential for the detection of changes in problem-gambling prevalence among online users.

OPEN SOURCE TEXTBOOK AS A RESOURCE FOR THE TEACHING-LEARNING PROCESS OF ALGEBRA IN INITIAL TRAINING OF MATHEMATICS TEACHERS

Objective: To determine the implications of the use of open source text in the teaching-learning process of algebraic structures in the initial teacher training of the mathematics specialty in a state university in Peru. Theoretical Framework: The conceptual and epistemic bases of open learning are systematically addressed through interactive texts, as well as the aspects related to the teaching-learning process in university higher education. Method: The study has a mixed approach, pre-experimental design and correlational level, the target population was mathematics education students and a sample of 46 randomly chosen students, data collection is carried out through a diagnostic questionnaire, another multiple alternative and an interview, in the study sample classes are held through the open source book; then the learning achieved at the conceptual level is evaluated. procedural of algebraic structures. Results and Discussion: In this research it is evident that students did not know the open source online text for the study of mathematics, but they have skills in the use of digital technology; but with the use of the digital book they assimilate the concepts, perform demonstrations and solve problems efficiently, raising their level of motivation towards learning. Thus, the relevant use of open source books significantly improves learning and the development of mathematical competence in students. Research Implications: Strengthening of interactive and personalized activities for a comprehensive training of mathematics content mediated by digital technology, reinforcing in a sustained way the culture and mathematical competence of teachers in initial training. Originality/Value: Implementation of an innovative approach in pedagogical practice, through the use of open resources for the assimilation of mathematical concepts and procedures in a dynamic, efficient and effective way. The value of research is evidenced in the praxis of didactic strategies in the context of the digital age, oriented to the knowledge of algebraic structures by mathematics teachers.

Nanotechnology-driven Microemulsion Based Intranasal Delivery to Neurotechnology-driven Neuralink: Strategies to Improve Management of Neurodegenerative Disorders.

Neurodegenerative disorder refers to malfunctioning of neuronstheirdegradation leading to death of neurons. Among various neurodegenerative disorders APHD (Alzheimer's, Parkinson's, and Huntington's Disease) are particularly concerning due to their progressive and debilitating nature. The therapeutic agent used for treatment and management of APHD often show unsatisfactory clinical outcome owing to poor solubility and limitedpermeability across blood brain barrier (BBB). The nose-to brain delivery can overcome this BBBchallenge as it can transport drug directly to brain though olfactory pathways bypassing BBB. Additionally, the nanotechnology has emerged as a cutting-edge methodology to address this issue and specifically mucoadhesive micro/nanoemulsion can improve the overall performance of the drug when administered intranasally. Beyond the therapy neurotechnology has emerged as are revolutionary AI-driven BCI (Brain computer interface) aimed to restore independence in patients with function loss due to neuron degeneration/death. A promising BCI Neuralink has been recently explored for clinical trials and results revealed that a quadriplegia bearing person with implanted Neuralink chip was able to perform few normal functions of daily routine such as playing online games, text messaging, reading, and learning foreign languages online through accessing the particular websites. This review will discuss the fundamental concepts of neurodegeneration, application of micro/nanoemulsion through intranasal route and integration of neurotechnology for the management and treatment of APHD.

Mind4Health: decolonizing gatekeeper trainings using a culturally relevant text message intervention.

When a person dies by suicide, it takes a reverberating emotional, physical, and economic toll on families and communities. The widespread use of social media among youth and adolescents, disclosures of emotional distress, suicidal ideation, intent to self-harm, and other mental health crises posted on these platforms have increased. One solution to address the need for responsive suicide prevention and mental health services is to implement a culturally-tailored gatekeeper training. The Northwest Portland Area Indian Health Board (NPAIHB) developed Mind4Health, an online gatekeeper training (90 min) and text message intervention for caring adults of American Indian/Alaska Native (AI/AN) youth. The Mind4Health intervention was a multi-phase, single-arm, pre-and post-test study of users enrolled in the intervention that is available via text message (SMS) or via a 90 min online, self-paced training. We produced four datasets in this study: Mobile Commons, pre-survey data, post-survey data, and Healthy Native Youth website's Google Analytics. The analysis included data cleaning, basic frequency counts, percentages, and descriptive statistics. Qualitative data were analyzed using thematic content analysis methods and hand-coding techniques with two independent coders. From 2022 to 2024, 280 people enrolled in the Mind4Health SMS training, and 250 completed the 8-week intervention. Many messages in the sequence were multi-part text messages and over 21,500 messages were sent out during the timeframe. Of the 280 subscribers, 52 participated in the pre-survey. Pre-survey data show that 94% of participants were female, and nearly one-fourth lived in Washington state, 92% of participants in the pre-survey were very to moderately comfortable talking with youth about mental health (n = 48). Most participants interact with youth in grades K-12. Post-survey data demonstrate changes in knowledge, beliefs, comfort talking about mental health, and self-efficacy among participants. Mind4Health improved participant's skills to have mental health conversations with youth and refer youth to resources in their community.

Hurtful Digital Communications In Hong Kong: Stakeholder Accounts

Hurtful digital communications (HDC) is an umbrella term referring to a wide variety of text and image-based practices online, such as cyberbullying or the non-consensual distribution of intimate images (NCDII). They can cause significant harm to victims and, as elsewhere, these practices are on the rise in Hong Kong. This paper represents the first stage of a project aimed at developing a coherent, broad-spectrum response to that rise. It discusses nine interviews with stakeholder groups or representatives in Hong Kong, revealing commonalities and themes in their experiences with clients who have been victims of HDC. While Hong Kong has recently adopted piecemeal reform of criminal laws targeting certain HDC practices such as ‘up-skirting’, NCDII, and doxing, these interviews suggest that these reforms alone are unlikely prove effective. Amongst other things, the interviews reveal a desire by victims not simply for punishment but resolution and restitution. Other jurisdictions have responded to these desires through the adoption both of expanded civil actions and broader regulatory regimes. This paper sets the groundwork for justifying similar reforms in Hong Kong. Keywords: Law, Technology, Cyberbullying, NCDII, Communications, Hong Kong, Privacy, Tort, Regulation

Smart Virtual Assistant Academic Model for a University Website

This paper presents the query chatbot system implemented by an institution, which is designed to deliver prompt and efficient responses to inquiries from both students and faculty members. Machine learning algorithms and natural language processing techniques were used in the creation of the chatbot. Using a dataset of commonly asked questions by students, we evaluated the system's functionality. The outcomes showed that the chatbot could deliver precise answers on schedule. The system's ability to provide prompt responses to often- asked questions might potentially save time for both teachers and pupils. Our study demonstrates the value of chatbots in educational environments and suggests avenues for further investigation into this area. A conversational buddy is a piece of software that facilitates online text or voice messaging conversations. They can contextualize human participation, making dialogue more interesting. A powerful tool for building chatbots that can serve as a college inquiry system is the Python framework Rasa X The goal of this research project is to establish guidelines for building a dynamic chatbot that can communicate with users via text and speech.

An attention approach to emoji focused sarcasm detection

Emojis play a nuanced role in digital communication and have a potential to convey sarcastic intent as they often offer non-explicit and sometimes ambiguous cues. This ambiguity has a potential to fuel hate-speech, trolling, or cyber-bullying under the guise of sarcasm. There have been numerous studies that employ modalities like audio, images, videos, emojis or a combination of modalities to detect sarcasm in online text. There is limited research that focuses solely on the impact of emojis in discerning sarcasm. Therefore, in this work we use popular attention networks to capture if sarcasm classification can be improved when emojis are present in text. We experiment with LSTM, Bi-LSTM, and attention networks and compare the results with the fine-tuned benchmark DeepMoji model. Our experiments demonstrate that the emojis can help improve sarcasm classification. These models outperform the benchmark DeepMoji model on two different test datasets on Matthew's correlation coefficient and Area under the curve metrics. Our proposed models surpass DeepMoji by an increase in 0.22 and 0.25 when compared for MCC and an increase in 13.3 % and 14.76 % for the ROC-AUC metric.

Developing ESP students’ online text reading performance and strategies in small group discussion

Developing ESP students’ online text reading performance and strategies in small group discussion

AI models collapse when trained on recursively generated data

Stable diffusion revolutionized image creation from descriptive text. GPT-2 (ref. 1), GPT-3(.5) (ref. 2) and GPT-4 (ref. 3) demonstrated high performance across a variety of language tasks. ChatGPT introduced such language models to the public. It is now clear that generative artificial intelligence (AI) such as large language models (LLMs) is here to stay and will substantially change the ecosystem of online text and images. Here we consider what may happen to GPT-{n} once LLMs contribute much of the text found online. We find that indiscriminate use of model-generated content in training causes irreversible defects in the resulting models, in which tails of the original content distribution disappear. We refer to this effect as ‘model collapse’ and show that it can occur in LLMs as well as in variational autoencoders (VAEs) and Gaussian mixture models (GMMs). We build theoretical intuition behind the phenomenon and portray its ubiquity among all learned generative models. We demonstrate that it must be taken seriously if we are to sustain the benefits of training from large-scale data scraped from the web. Indeed, the value of data collected about genuine human interactions with systems will be increasingly valuable in the presence of LLM-generated content in data crawled from the Internet.

Sparking creativity: Encouraging creative idea generation through automatically generated word recommendations

Creative block is a familiar foe to any who attempt to create and is especially related to “writers block”. While significant effort has been focused on developing methods to break such blocks, it remains an active challenge. Here, we focus on the role of semantic memory structure in driving creative block, by having people get “stuck” in a certain part of their semantic memory network. We directly examine whether we can “pull out” a participant from where they got “stuck” in their semantic memory, breaking their creative impasse. Our Associative Creativity Sparker (ACS) is a cognitive network science-based online tool that aims to spark creative ideas and break creative impasse: Once a participant runs out of ideas in a creative idea generation task, word recommendations are suggested to prime new ideas. These word recommendations are either towards or away from previous ideas, as well as close or far from the target object, based on a conceptual space extracted from the participants responses using online text analysis. In Study 1, 121 participants use the ACS to generate creative alternative uses for five different objects and completed creativity and Gf tasks. In Study 2, we repeat the design of Study 1, but further examine the impact of writing experience on the ACS, by examining 120 novice and 120 experienced writers. Across both studies, our results indicate that the location of word recommendations affects the fluency and originality of one’s ideas, and that novice and experienced writers differently benefit from these word recommendations.

Using Internet Reciprocal Teaching to Develop Second Graders’ Online Text Evaluation Skills

The current study examined the actions and thought processes second grade students go through while reading online, implementing a research based teaching strategy for new literacies, Internet Reciprocal Teaching (IRT). In particular, strategies for how to critically evaluate online text were introduced to the second grade students. Through IRT, second graders were able to  evaluate online texts for relevance and credibility. Participants used several different strategies in determining credibility of online texts. They sought out more information about the website or author, used background knowledge about a particular website, looked at the URL, identified the amount of ads on a webpage, and used other miscellaneous criteria. The current study can contribute to existing literature by exploring evaluation strategies that young students may already possess and addressing any possible relationships between IRT and evaluation strategies used by students while reading on the internet.

Publication performance and trends in psychological capital research: a bibliometric analysis

PurposeThis research aims to provide a comprehensive understanding of the evolution and trends in psychological capital (PsyCap) research and related issues.Design/methodology/approachThis research uses bibliometric analysis. A total of 2,244 journal articles were extracted from the Scopus database using relevant keywords, covering the period from 1997 to 2023. The data analysis was conducted utilizing VOSviewer software, Microsoft Excel, and an online text analysis tool.FindingsThere is a rapid rise in the quantity of PsyCap publications, especially from 2017, with significant contribution of research from Chinese scholars with 577 articles in the period 2019–2023. The antecedents of PsyCap have a stagnation of leadership-related topics and increased focus on social support and perceived organizational support. The attention has been specifically directed toward well-being and mental health, with special emphasis on work engagement, job satisfaction, and job performance.Research limitations/implicationsThe exclusion of certain publications in this research may overlook emerging trends. Thus, future research endeavors should adopt a multifaceted approach that combines bibliometric analysis with qualitative and quantitative methods to glean comprehensive insights into PsyCap research.Originality/valuePsyCap research is growing rapidly, with more publications in the last three years than in all the previous years combined. This study, updating data until the end of 2023, provides the most up-to-date insights on research trends in PsyCap to aid scholars in discerning suitable avenues for their research endeavors.

Analysis of Lexical Density and Readability of Pakistani English Newspaper Dawn

This research study aimed to analyze the lexical density and readability of Pakistani English Newspaper and so, to suggest their suitability for the level of students. Eight newspapers from four genres were selected as sample. The theory of Systemic Functional Linguistics based on the theory of lexical density by Ure (1971) was applied for finding lexical density and readability indices by using content analysis design through an online text analyzer software. Readability values were compared with the FleschmReading Ease Scale. The results of this study showed that lexical density values of all genres were greater than 40% according to the Flesch Reading Ease Scale. All the texts were lexically dense having a greater number of contents carrying lexical items as compared to grammatical items. The findings of study could also be applied to academic textbooks in order to check complexity and suitability according to the level of the students.

Play Well Triple P: Developing and Evaluating a Program to Promote Positive Parental Involvement in Junior Sport.

Parents play a central role in children's ongoing participation and enjoyment of sport. Despite compelling evidence that parental behaviour can undermine the quality of children's experiences in sport, little research has examined whether strategies to support parents to engage in positive sports parenting behaviour are effective. In this paper, we report two studies that had the overall aim of developing, implementing and evaluating a program designed to promote positive parental involvement and improve spectator behaviour in junior rugby league in Australia. Study 1 involved the development of a prototype version of the program, named Play Well Triple P, which was qualitatively evaluated through interviews with 19 parents about their satisfaction with the program. In Study 2, we used feedback from Study 1 to refine the program and develop a pilot version, which was then evaluated in a quasi-experimental feasibility study with 101 parents (mean age = 38.42 years; 72% mothers) of junior rugby league players. The pilot version involved one interactive online module and text messages to reinforce content and prompt strategy implementation across the season. Participation in Play Well Triple P was associated with increased positive sports parenting behaviour and reduced controlling and intrusive sports parenting behaviour, with a trend towards reducing over-reactive parenting practices at home. These findings are discussed in relation to the feasibility of implementing a brief and engaging sports parenting intervention in the context of a broader integrated system designed to facilitate ongoing participation of children in sport.

Learning Dynamic Multimodal Network Slot Concepts from the Web for Forecasting Environmental, Social and Governance Ratings

Dynamic multimodal networks are networks with node attributes from different modalities where the attributes and network relationships evolve across time, i.e., both networks and multimodal attributes are dynamic; for example, dynamic relationship networks between companies that evolve across time due to changes in business strategies and alliances, which are associated with dynamic company attributes from multiple modalities such as textual online news, categorical events, and numerical financial-related data. Such information can be useful in predictive tasks involving companies. Environmental, social, and governance (ESG) ratings of companies are important for assessing the sustainability risks of companies. The process of generating ESG ratings by expert analysts is, however, laborious and time-intensive. We thus explore the use of dynamic multimodal networks extracted from the web for forecasting ESG ratings. Learning such dynamic multimodal networks from the web for forecasting ESG ratings is, however, challenging due to its heterogeneity and the low signal-to-noise ratios and non-stationary distributions of web information. Human analysts cope with such issues by learning concepts from past experience through relational thinking and scanning for such concepts when analyzing new information about a company. In this article, we propose the Dynamic Multimodal Slot Concept Attention-based Network (DynScan) model. DynScan utilizes slot attention mechanisms together with slot concept alignment and disentanglement loss functions to learn latent slot concepts from dynamic multimodal networks to improve performance on ESG rating forecasting tasks. DynScan is evaluated on forecasting tasks on six datasets, comprising three ESG ratings across two sets of companies. Our experiments show that DynScan outperforms other state-of-the-art models on these forecasting tasks. We also visualize the slot concepts learned by DynScan on five synthetic datasets and three real-world datasets and observe distinct and meaningful slot concepts being learned by DynScan across both synthetic and real-world datasets.

Demand and satisfaction analysis of short health videos among Chinese urban youth: A mixed-methods study based on the KANO model

Short videos have become a powerful medium in health communication. This study explores the information needs and satisfaction of Chinese urban youth regarding short health videos, guided by the KANO model. The research was conducted in four stages: text mining, online survey, demand analysis, and emotional strategy analysis. During the text mining stage, we used GooSeeker software to extract 26,108 health-tagged short video entries from Douyin and identified 21 unique themes through a collinear network analysis. In the online survey stage, we gathered data on urban youth’s preferences for these themes. Using the KANO model and Better-Worse analysis in the demand analysis stage, we categorized health video demands and gained insights into the preferred content. In the emotional strategy analysis stage, we examined how different emotional strategies like appeals to fear and hope influenced content effectiveness. Findings show that content related to health science, tea drinking, popular news, and food safety significantly enhances satisfaction. Conversely, information on refuting rumors, epidemic prevention, and control, as well as authoritative views, tends to lower satisfaction, possibly due to a trust crisis caused by a mismatch between demand and supply. This study suggests that content creators can boost engagement and satisfaction by focusing on preferred themes. It also highlights the varying impacts of information sources and emotional strategies on the health video preferences of Chinese urban youth. The insights from this research provide a foundation for user-centric content creation and platform development in health communication.