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The purpose of this article is to examine the structure and determine the MDA framework for use in the development and design of library websites. The topic of innovation in libraries is frequently discussed; thus, we have tried to offer techniques for innovation in website design for libraries.

This study compares these two approaches to determine if the mechanical, dynamic and aesthetic (MDA) framework can also be used to create library websites. Each of the MDA framework’s three components was assessed for their applicability to the development of a library website.

When building a library website, three crucial characteristics that must be carefully taken into account are, among other things, being supporting and safety-oriented; adaptable and accessible; and aesthetically pleasing to the user. Studies have also revealed several additional criteria that may be regarded as success factors for library websites. In addition, there is also a framework for creating touch- and gesture-based interactions. It is also a method for understanding the creation and playing of video games. The acronym MDA stands for the three components of its structure: mechanical, dynamic and aesthetic.

Many kinds of library websites exist, including those for academic, public, school and special libraries. So far, models and approaches for designing pages have been offered for each of these library website categories.

There is a need for technology that can protect scientific findings as a unique asset but is this possible? Non-fungible tokens (NFTs) are one possible solution.

Plagiarism is an unethical act and a violation of acceptable practices in the field of scholarly research and writing. Over the years, effective tools have been created to prevent and minimize plagiarism, especially through the integration of artificial intelligence technology to identify copied text. However, there is still scientific plagiarism of contents (such as articles, inventions or other digital objects).

NFTs are unique digital identifiers that use blockchain technology to ensure ownership rights of an object are maintained. NFT is a blockchain derivative that first entered the world of digital currencies and has now entered other areas, such as economy, fashion, music and computer games.

In this essay, how this technology may be useful to preventing acts of academic plagiarism is discussed.

The purpose of this paper is to examine the motivation behind Google’s development of Gemini and its potential impact on the information industry.

This viewpoint paper relies on a comprehensive analysis of the advancements in artificial intelligence (AI) technology, specifically in the field of chatbots.

The findings reveal that Gemini is designed to enhance user experiences by providing personalized and contextually relevant information. It aims to streamline information retrieval, improve customer service and offer tailored content recommendations. The competition among companies in building AI-powered chatbots is driving rapid advancements and innovation in the field.

The originality of this paper lies in its analysis of Google DeepMind’s Gemini and its potential impact on the information industry. It highlights the significance of AI-powered chatbots in transforming how users access and interact with information. This paper contributes to the existing literature by examining the competition in building AI tools and its implications for the future of the information industry. It offers insights into the motivation behind Google’s development of Gemini and its potential value in enhancing user experiences and driving monetization opportunities.

ChatGPT from OpenAI is an amazing example of machine learning technology. This technology has now become an important issue for high-tech plagiarism concern. Indeed, there are many concerns about using this tool, perhaps using other technologies to make ChatGPT safer. Non-fungible tokens (NFTs) may be a way out. This paper aims to discuss such an alternative.

To preventing with high-tech plagiarism created by the ChatGPT tool two ways can help schools, universities and scientific centers to prevent academic plagiarism: first, by banning ChatGPT and adjusting teaching styles, and second, by using detecting AI-produced content. In this viewpoint, the authors suggest a third way that can be a way out.

NFTs technology has the ability to add a non-fungibility feature to any digital object (image, text or video). Therefore, any text produced by artificial intelligence tools can be given a specific NFT code. With this work, the authors add a feature to texts produced by artificial intelligence, that is, the non-fungibility feature.

In this viewpoint, how and why NFTs may be a usefully added value in preventing acts of high-tech plagiarism on ChatGPT is discussed.

In this study, the authors seek to introduce ways that show that in the age of artificial intelligence (AI), selective dissemination of information (SDI) performance can be greatly enhanced by leveraging AI technologies and algorithms.

AI holds significant potential for the SDI. In the age of AI, SDI can be greatly enhanced by leveraging AI technologies and algorithms. The authors discuss SDI technique used to filter and distribute relevant information to stakeholders based on the pertinent modern literature.

The following conceptual indicators of AI can be utilized for obtaining a better performance measure of SDI: intelligent recommendation systems, natural language processing, automated content classification, contextual understanding, intelligent alert systems, real-time information updates, intelligent alert systems, real-time information updates, adaptive learning, content summarization and synthesis.

The authors propose the general framework in which AI can greatly enhance the performance of SDI but also emphasize that there are challenges to consider. These include ensuring data privacy, avoiding algorithmic biases, ensuring transparency and accountability of AI systems and addressing concerns related to information overload.

The study aims to analyze the synergy of artificial intelligence (AI), with scientometrics, webometrics and bibliometrics to unlock and to emphasize the potential of the applications and benefits of AI algorithms in these fields.

By conducting a systematic literature review, our aim is to explore the potential of AI in revolutionizing the methods used to measure and analyze scholarly communication, identify emerging research trends and evaluate the impact of scientific publications. To achieve this, we implemented a comprehensive search strategy across reputable databases such as ProQuest, IEEE Explore, EBSCO, Web of Science and Scopus. Our search encompassed articles published from January 1, 2000, to September 2022, resulting in a thorough review of 61 relevant articles.

(1) Regarding scientometrics, the application of AI yields various distinct advantages, such as conducting analyses of publications, citations, research impact prediction, collaboration, research trend analysis and knowledge mapping, in a more objective and reliable framework. (2) In terms of webometrics, AI algorithms are able to enhance web crawling and data collection, web link analysis, web content analysis, social media analysis, web impact analysis and recommender systems. (3) Moreover, automation of data collection, analysis of citations, disambiguation of authors, analysis of co-authorship networks, assessment of research impact, text mining and recommender systems are considered as the potential of AI integration in the field of bibliometrics.

This study covers the particularly new benefits and potential of AI-enhanced scientometrics, webometrics and bibliometrics to highlight the significant prospects of the synergy of this integration through AI.

The purpose of this study is to raise awareness about the ethical implications of artificial intelligence (AI) in the library and information industry, specifically focusing on bias and discrimination. It aims to highlight the need for proactive measures to mitigate these issues and ensure that AI technology is developed and implemented in an ethical and unbiased manner.

This viewpoint paper presents a critical analysis of the ethical implications of bias and discrimination in the library and information industry with respect to AI. It explores current practices and challenges in AI implementation and proposes strategies to address bias and discrimination in AI systems.

The findings of this study reveal that bias and discrimination are significant concerns in AI systems used in the library and information industry. These biases can perpetuate existing inequalities, hinder access to information and reinforce discriminatory practices. This study identifies key strategies such as data collection and representation, algorithmic transparency and inclusive design to address these issues.

This study contributes to the existing literature by examining the specific challenges of bias and discrimination in AI implementation within the library and information industry. It provides valuable insights into the ethical implications of AI technology and offers practical recommendations for professionals to confront and mitigate bias and discrimination in AI systems, ensuring equitable access to information for all users.