Hasil untuk "Bibliography. Library science. Information resources"

Alisa Muharemagić

Aim: The aim of the research was to assess the state of library activities and provide recommendations for improvement in accordance with the Library Activity Law of Tuzla Canton and international standards. Methodology: The methodological approach is entirely innovative and the first of its kind in Tuzla Canton, and it can serve as a model for other cantons in the Federation of Bosnia and Herzegovina. This methodological approach combines: quantitative analysis (statistical data, numerical indicators), qualitative assessment (field visits, interviews), formalized documentation (minutes with recommendations), and systematic monitoring of implementation. Results: The result of the analysis of the collected data indicates significant deficiencies in the functioning of libraries, including inadequate funding, insufficient number of professional staff, and weak connectivity with modern library-information systems, as prerequisites for compliance with legal regulations. Social significance: By achieving social significance, it is expected that this work will encourage similar initiatives in other cantons, serve as reference material for policy makers, contribute to the standardization of approaches to coordinating library services in Bosnia and Herzegovina, and be cited in future library research, as the work proposes specific measures to improve the overall state of libraries and their integration into the COBISS system. Practical application: From a practical application perspective, the work proposes systemic measures through urgent, medium-term, and long-term interventions, including increasing budgetary expenditures, technological modernization, and staff strengthening. Originality: This professional paper represents the first comprehensive analysis of the state of the library network in Tuzla Canton based on professional supervision conducted in the period 2023–2024. The research covers 22 libraries of different types: nine public libraries, three special libraries, and thirteen organizational units of the University Library, as well as continuous monitoring of over 131 libraries through dossiers.

Mizanur Rahman, Amran Bhuiyan, Mohammed Saidul Islam et al.

Recent advances in large language models (LLMs) have enabled a new class of AI agents that automate multiple stages of the data science workflow by integrating planning, tool use, and multimodal reasoning across text, code, tables, and visuals. This survey presents the first comprehensive, lifecycle-aligned taxonomy of data science agents, systematically analyzing and mapping forty-five systems onto the six stages of the end-to-end data science process: business understanding and data acquisition, exploratory analysis and visualization, feature engineering, model building and selection, interpretation and explanation, and deployment and monitoring. In addition to lifecycle coverage, we annotate each agent along five cross-cutting design dimensions: reasoning and planning style, modality integration, tool orchestration depth, learning and alignment methods, and trust, safety, and governance mechanisms. Beyond classification, we provide a critical synthesis of agent capabilities, highlight strengths and limitations at each stage, and review emerging benchmarks and evaluation practices. Our analysis identifies three key trends: most systems emphasize exploratory analysis, visualization, and modeling while neglecting business understanding, deployment, and monitoring; multimodal reasoning and tool orchestration remain unresolved challenges; and over 90% lack explicit trust and safety mechanisms. We conclude by outlining open challenges in alignment stability, explainability, governance, and robust evaluation frameworks, and propose future research directions to guide the development of robust, trustworthy, low-latency, transparent, and broadly accessible data science agents.

WANG Weizheng, QIAO Hong, LI Xiaojun, WANG Jingjing

[Purpose/Significance] Generative artificial intelligence (AI) technology has been widely used in many fields, and the application of this technology has become popular among researchers. However, there are few studies on the willingness of researchers willingness to accept generative AI. This leads to an insufficient understanding of the psychological mechanism, cognitive process and behavioral pattern of users' acceptance of generative AI, which limits the ability of theoretical innovation and practical exploration in user information behavior. This study focuses on researchers acceptance of generative AI. By studying the evaluation process of ChatGPT by college students, it explores the acceptance behavior of generative AI. At the same time, it verifies the applicability of the AIDUA model in the new context, and introduces the new variable of school identity, which further extends the AIDUA model. [Method/Process] Based on the cognitive assessment theory and the AI acceptance framework (AIDUA), this paper constructs a theoretical model of the intention to use generative artificial intelligence, and develops and empirically tests the theoretical model of the intention to use generative AI. Taking college students as the main research object, based on the maturity scale in authoritative literature at home and abroad, 8 variables and 29 observation variables such as social influence, hedonic motivation and anthropomorphism were designed. College students with experience in using generative AI were invited to participate in the questionnaire survey. SPSS26.0 was used to analyze the data from 294 valid questionnaires collected. SmartPLS 3.2.9 was used to construct a structural equation model to test the hypothesis, and the JN method was used to detect the regulatory effect. [Results/Conclusions] The study found that users went through three stages of decision making before using generative AI. The PLS-SEM results show that: 1) Social influence, hedonic motivation and anthropomorphism significantly affect performance expectancy and effort expectancy, and anthropomorphism is the strongest variable affecting performance expectancy and effort expectancy. 2) Performance expectancy and effort expectancy are significantly negatively correlated with negative emotions, while hedonic motivation has no significant effect on negative emotions. 3) Negative emotions are significantly negatively correlated with users' intension to use. 4) School identity moderates the relationship between effort expectancy and negative emotions. This study combines anthropomorphic research on college students' acceptance of generative AI, and provides a framework for the acceptance of generative AI. Researchers can use this framework to better study the acceptance of AI. This study has some limitations. In the future, we will focus on the following three aspects: 1) to evaluate the users' acceptance of generative AI in different usage scenarios. 2) to use samples of other groups to test the applicability of the model, such as civil servants, librarians, researchers and other groups. 3) to incorporate variables from other technology acceptance models into the model, such as ease of use and practicality.

Xiufeng Xu, Fuman Xie, Chenguang Zhu et al.

Modern AI- and Data-intensive software systems rely heavily on data science and machine learning libraries that provide essential algorithmic implementations and computational frameworks. These libraries expose complex APIs whose correct usage has to follow constraints among multiple interdependent parameters. Developers using these APIs are expected to learn about the constraints through the provided documentations and any discrepancy may lead to unexpected behaviors. However, maintaining correct and consistent multi-parameter constraints in API documentations remains a significant challenge for API compatibility and reliability. To address this challenge, we propose MPDetector, for detecting inconsistencies between code and documentation, specifically focusing on multi-parameter constraints. MPDetector identifies these constraints at the code level by exploring execution paths through symbolic execution and further extracts corresponding constraints from documentation using large language models (LLMs). We propose a customized fuzzy constraint logic to reconcile the unpredictability of LLM outputs and detects logical inconsistencies between the code and documentation constraints. We collected and constructed two datasets from four popular data science libraries and evaluated MPDetector on them. The results demonstrate that MPDetector can effectively detect inconsistency issues with the precision of 92.8%. We further reported 14 detected inconsistency issues to the library developers, who have confirmed 11 issues at the time of writing.

Kaan Kale, Homa Esfahanizadeh, Noel Elias et al.

With the exponential growth in data volume and the emergence of data-intensive applications, particularly in the field of machine learning, concerns related to resource utilization, privacy, and fairness have become paramount. This paper focuses on the textual domain of data and addresses challenges regarding encoding sentences to their optimized representations through the lens of information-theory. In particular, we use empirical estimates of mutual information, using the Donsker-Varadhan definition of Kullback-Leibler divergence. Our approach leverages this estimation to train an information-theoretic sentence embedding, called TexShape, for (task-based) data compression or for filtering out sensitive information, enhancing privacy and fairness. In this study, we employ a benchmark language model for initial text representation, complemented by neural networks for information-theoretic compression and mutual information estimations. Our experiments demonstrate significant advancements in preserving maximal targeted information and minimal sensitive information over adverse compression ratios, in terms of predictive accuracy of downstream models that are trained using the compressed data.

Zhenya Huang, Yuting Ning, Longhu Qin et al.

Educational resource understanding is vital to online learning platforms, which have demonstrated growing applications recently. However, researchers and developers always struggle with using existing general natural language toolkits or domain-specific models. The issue raises a need to develop an effective and easy-to-use one that benefits AI education-related research and applications. To bridge this gap, we present a unified, modularized, and extensive library, EduNLP, focusing on educational resource understanding. In the library, we decouple the whole workflow to four key modules with consistent interfaces including data configuration, processing, model implementation, and model evaluation. We also provide a configurable pipeline to unify the data usage and model usage in standard ways, where users can customize their own needs. For the current version, we primarily provide 10 typical models from four categories, and 5 common downstream-evaluation tasks in the education domain on 8 subjects for users' usage. The project is released at: https://github.com/bigdata-ustc/EduNLP.

Brian Wright, Peter Alonzi, Ali Rivera

The definition of Data Science is a hotly debated topic. For many, the definition is a simple shortcut to Artificial Intelligence or Machine Learning. However, there is far more depth and nuance to the field of Data Science than a simple shortcut can provide. The School of Data Science at the University of Virginia has developed a novel model for the definition of Data Science. This model is based on identifying a unified understanding of the data work done across all areas of Data Science. It represents a generational leap forward in how we understand and teach Data Science. In this paper we will present the core features of the model and explain how it unifies various concepts going far beyond the analytics component of AI. From this foundation we will present our Undergraduate Major curriculum in Data Science and demonstrate how it prepares students to be well-rounded Data Science team members and leaders. The paper will conclude with an in-depth overview of the Foundations of Data Science course designed to introduce students to the field while also implementing proven STEM oriented pedagogical methods. These include, for example, specifications grading, active learning lectures, guest lectures from industry experts and weekly gamification labs.

O. Lavrik

Search and development of library activity areas, when it is no more the only custodian of information, and the organization, which provides access to it, is one of the pressing present problems. Scientific libraries have long been engaged in the popularization of science. Now, besides popularization, in the relations between science and society, one highlights the understanding of science and the involving of public in science, as well. The author analyzes the existing forms of library activities on the example of ethical problems of science from the viewpoint of their suitability for the main areas of interaction between science and the public. The author comes to following the conclusions: 1) the advantages of acceptable forms are their high quality due to the invitation of researchers to participate; control over the agenda (the event plan); the ability to select an audience (it can be very big); direct communication; inclusion of external partners as experts and the ability to record the event and to demonstrate it via Internet. The disadvantages can be the difficulty to control the perception of information (there is no complete control by researchers; dependence on the resources of organization; the need for additional work to attract readers; possession of communication skills; 2) almost all forms of library work are suitable for science popularization. Much fewer ones can be used for understanding scientific phenomena and results. At the same time, all of them require direct participation of scientists. Any form (besides databases and repositorium) can be used to involve the general public into science. For different purposes in this area, different forms are necessary; 3) created in libraries repositories and scientific databases are controlled by scientists poorly. They can be used not only by scientists, thus increasing the possibility of misinterpretation by society; 4) when creating advisory bibliographic resources the position of the expert selecting and advising popular science literature, is important, as well as the opinion of the readers who have the opportunity to post their viewpoint on any advises document.

Peace Ossom Williamson, C. Minter

Objective PubMed’s provision of MEDLINE and other National Library of Medicine (NLM) resources has made it one of the most widely accessible biomedical resources globally. The growth of PubMed Central (PMC) and public access mandates have affected PubMed’s composition. The authors tested recent claims that content in PMC is of low quality and affects PubMed’s reliability, while exploring PubMed’s role in the current scholarly communications landscape. Methods The percentage of MEDLINE-indexed records was assessed in PubMed and various subsets of records from PMC. Data were retrieved via the National Center for Biotechnology Information (NCBI) interface, and follow-up interviews with a PMC external reviewer and staff at NLM were conducted. Results Almost all PubMed content (91%) is indexed in MEDLINE; however, since the launch of PMC, the percentage of PubMed records indexed in MEDLINE has slowly decreased. This trend is the result of an increase in PMC content from journals that are not indexed in MEDLINE and not a result of author manuscripts submitted to PMC in compliance with public access policies. Author manuscripts in PMC continue to be published in MEDLINE-indexed journals at a high rate (85%). The interviewees clarified the difference between the sources, with MEDLINE serving as a highly selective index of journals in biomedical literature and PMC serving as an open archive of quality biomedical and life sciences literature and a repository of funded research. Conclusion The differing scopes of PMC and MEDLINE will likely continue to affect their overlap; however, quality control exists in the maintenance and facilitation of both resources, and funding from major grantors is a major component of quality assurance in PMC.

Vanessa Irvin, Sarah Nakashima

This paper presents an inquiry-based pedagogical approach to teaching the reference interview and query search process for the reference course in the library and information science (LIS) curriculum. The Query Search Method (QSM) is a methodology grounded within a theoretical framework that synthesizes the tenets of literacy studies, critical librarianship, and librarian practitioner inquiry. In the reference course at two ALA-accredited library science programs, the QSM was employed as an iterative search process that actively applies advanced search techniques with online public access catalogs, subscription databases, bibliographic networks, web-based search engines and other online resources. The QSM can be taught in reference courses to fortify pre-service librarians with strong search skills that incorporate social skills that are socio-culturally competent with a critical lens and are immediately usable across various platforms, bridging the gap between library users’ access to and use of contemporary technologies as literate citizens in an interconnected digital world.

Douglas Beck, Joseph Carlson, Zohreh Davoudi et al.

In preparation for the 2023 NSAC Long Range Plan (LRP), members of the Nuclear Science community gathered to discuss the current state of, and plans for further leveraging opportunities in, QIST in NP research at the Quantum Information Science for U.S. Nuclear Physics Long Range Planning workshop, held in Santa Fe, New Mexico on January 31 - February 1, 2023. The workshop included 45 in-person participants and 53 remote attendees. The outcome of the workshop identified strategic plans and requirements for the next 5-10 years to advance quantum sensing and quantum simulations within NP, and to develop a diverse quantum-ready workforce. The plans include resolutions endorsed by the participants to address the compelling scientific opportunities at the intersections of NP and QIST. These endorsements are aligned with similar affirmations by the LRP Computational Nuclear Physics and AI/ML Workshop, the Nuclear Structure, Reactions, and Astrophysics LRP Town Hall, and the Fundamental Symmetries, Neutrons, and Neutrinos LRP Town Hall communities.

Kamber Schwarz, Joan Najita, Jennifer Bergner et al.

The Orbiting Astronomical Satellite for Investigating Stellar Systems (OASIS) is a NASA Astrophysics MIDEX-class mission concept, with the stated goal of following water from galaxies, through protostellar systems, to Earth's oceans. This paper details the protoplanetary disk science achievable with OASIS. OASIS's suite of heterodyne receivers allow for simultaneous, high spectral resolution observations of water emission lines spanning a large range of physical conditions within protoplanetary disks. These observations will allow us to map the spatial distribution of water vapor in disks across evolutionary stages and assess the importance of water, particularly the location of the midplane water snowline, to planet formation. OASIS will also detect the H2 isotopologue HD in 100+ disks, allowing for the most accurate determination of total protoplanetary disk gas mass to date. When combined with the contemporaneous water observations, the HD detection will also allow us to trace the evolution of water vapor across evolutionary stages. These observations will enable OASIS to characterize the time development of the water distribution and the role water plays in the process of planetary system formation.

Zeni Istiqomah

Background of the study: The library of SMA Muhammadiyah 1 Yogyakarta has a unique and distinctive collection that is referred to as local content and organized in Muhi Corner. Libraries have a duty to collect and disseminate them to users Purpose: This study aims to analyze the local content information service of Muhi Corner, analyze the information dissemination process carried out, and evaluate the obstacles in the dissemination of information. Method: This study uses a qualitative approach with a descriptive method. Data were collected through observation, interviews, and documentation analysis. The data analysis was conducted by data reduction, data presentation, and conclusion. Findings: The results showed that Information dissemination activities for Muhi Corner's collections started with information dissemination for teachers, education staff, students, and researchers; then packaged in the form of print and digital papers. Information sources are presented in the form of local collections and gray literature. The information channels used are direct (socialization & library tour) and social media (Instagram). Conclusion: Dissemination of information on the Muhi Corner collection has been carried out but is still limited, either directly or using the media. Obstacles in disseminating Muhi Corner information include, (1) limited human resources, (2) limited collection on the subject of literature, and (3) limited promotional activities.

Rachid Ettaoufiki, M'barek EL HALOUI, Mina ELMAALLAM

Le présent papier se propose à travers une revue de littérature d’analyser la situation actuelle de l’usage des Big Data par la statistique officielle, y compris les nouvelles tendances, les opportunités et les menaces. Les principaux apports des Big data seraient de permettre la production d’indicateurs statistiques à un niveau de détail élevé, dans des délais plus courts, à des coûts moindre et avec moins de charge sur les répondants. Néanmoins, certains défis sont à tenir en compte, notamment l’accès aux données, l’acquisition de nouvelles compétences et la protection des données personnelles des répondants. L’un des principaux objectifs de notre étude est d’analyser, à travers la revue des initiatives, les types d’indicateurs statistiques pouvant bénéficier de l’introduction des Big Data et les technologies Big Data ayant un potentiel statistique en mettant l’accent sur les risques, les défis et les opportunités. Le potentiel statistique des sources Big Data, notamment, les données des téléphones mobiles, les données de caisse, les données de l’imagerie satellitaire, et les données du webscraping a été examiné.

Iñigo Martinez, Elisabeth Viles, Igor G. Olaizola

In recent years, the data science community has pursued excellence and made significant research efforts to develop advanced analytics, focusing on solving technical problems at the expense of organizational and socio-technical challenges. According to previous surveys on the state of data science project management, there is a significant gap between technical and organizational processes. In this article we present new empirical data from a survey to 237 data science professionals on the use of project management methodologies for data science. We provide additional profiling of the survey respondents' roles and their priorities when executing data science projects. Based on this survey study, the main findings are: (1) Agile data science lifecycle is the most widely used framework, but only 25% of the survey participants state to follow a data science project methodology. (2) The most important success factors are precisely describing stakeholders' needs, communicating the results to end-users, and team collaboration and coordination. (3) Professionals who adhere to a project methodology place greater emphasis on the project's potential risks and pitfalls, version control, the deployment pipeline to production, and data security and privacy.

Sohyeon Hwang, Emőke-Ágnes Horvát, Daniel M. Romero

The public interest in accurate scientific communication, underscored by recent public health crises, highlights how content often loses critical pieces of information as it spreads online. However, multi-platform analyses of this phenomenon remain limited due to challenges in data collection. Collecting mentions of research tracked by Altmetric LLC, we examine information retention in the over 4 million online posts referencing 9,765 of the most-mentioned scientific articles across blog sites, Facebook, news sites, Twitter, and Wikipedia. To do so, we present a burst-based framework for examining online discussions about science over time and across different platforms. To measure information retention we develop a keyword-based computational measure comparing an online post to the scientific article's abstract. We evaluate our measure using ground truth data labeled by within field experts. We highlight three main findings: first, we find a strong tendency towards low levels of information retention, following a distinct trajectory of loss except when bursts of attention begin in social media. Second, platforms show significant differences in information retention. Third, sequences involving more platforms tend to be associated with higher information retention. These findings highlight a strong tendency towards information loss over time - posing a critical concern for researchers, policymakers, and citizens alike - but suggest that multi-platform discussions may improve information retention overall.

L. A. Mandrinina, V. Rykova

The article provides a brief overview of library local lore activity with an emphasis on the local lore direction in book studies and bibliography of the Siberian- Far Eastern region; names organizations providing information support for local lore activities of libraries; lists local lore resources on the websites of regional libraries in Siberia and the Far East. Special attention is paid to the resources generated by the State Public Scientific Technological Library of Siberian Branch of the Russian Academy of Sciences, which is the center for information support of local history research in Asian Russia, and obtains unique techniques to create regional databases, as well as highly qualified specialists. It presents a list of databases providing information support of theoretical and practical aspects of local history activity in the regional libraries. Authors give a detailed description of DB “Scientific Sibirika”, which includes regional material on a wide range of local history: history, ethnography, economy, nature and natural resources of certain territories of Siberia and the Far East, Arctic. It is shown that theoretical and methodological research in the field of library local history, individual persons, are presented in the “professional” DB “Librarianship and bibliography in Siberia and the Far East”, which has a special heading “Local lore activities of libraries in Siberia and the Far East”; the bibliologic direction of local lore is implemented in the bibliographic DB “History of books and book business in Siberia and the Far East”. The paper concludes about the importance of library local history in the library activities, and the need to attract information resources of large libraries for more complete implementation of local history research.

Edith Sáenz-Flores, Rubén Alfonso Saucedo-Terán, Carlos Raúl Morales-Nieto et al.

Una de las principales limitantes para la resiembra de pastizales en zonas áridas y semiáridas es la baja disponibilidad de semilla de zacates forrajeros. Además, existe poca información sobre la producción de semilla de zacates en México. El objetivo fue evaluar el efecto de la fertilización sobre la producción y calidad de semilla de cinco zacates forrajeros. La investigación se realizó en el Sitio Experimental La Campana del INIFAP, ubicado en el km 33.3 carretera Chihuahua-Ojinaga. Las especies evaluadas fueron: zacate navajita (Bouteloua gracilis), banderita (Bouteloua curtipendula), gigante (Leptochloa dubia), buffel (Pennisetum ciliare) y garrapata (Eragrostis superba). Los tratamientos incluyeron la fertilización química con 120-60-00, 60-30-00, 60- 30-00 + micorriza, fertilizante de liberación lenta, fertilizante orgánico y el testigo. Las unidades experimentales fueron parcelas de campo de 12 m2 distribuidas bajo un diseño de bloques al azar con tres repeticiones. Se estimó la producción de semilla, germinación de semilla y producción de forraje. En general, la mayor (P 0.05) producción de semilla en las cinco especies se obtuvo con los tratamientos 120-60-00 y 60-30-00 + micorriza, con valores desde 289 kg ha-1 en zacate navajita con la dosis 120-60-00 hasta 1,619 kg ha-1 en zacate garrapata con el tratamiento 60-30-00 + micorriza. El fertilizante de liberación lenta y la dosis 60-30-00 mostraron los porcentajes más altos (P 0.05) de germinación de semilla, con 14.5% en zacate navajita hasta 96.5% en gigante, ambos con fertilizante de liberación lenta. Algunos fertilizantes incrementaron el rendimiento y germinación de semilla y la producción de forraje. Abstract One of the main limiting factors for grassland seeding programs in arid and semiarid regions is the low seed availability of forage grasses. Furthermore, there exists little information on seed production of grasses species in Mexico. The objective was to evaluate the effect of fertilization on seed production and germination of five forage grass species. Research was conducted at INIFAP-La Campana Experimental station, located in Aldama, Chihuahua, km 33.3 Chihuahua-Ojinaga highway. Species studied were: blue grama (Bouteloua gracilis), sideoats grama (Bouteloua curtipendula), green sprangletop (Leptochloa dubia), buffel grass (Pennisetum ciliare), and wilman lovegrass (Eragrostis superba). Treatments were chemical fertilization at 120-60-00, 60-30-00, 60-30-00 + mycorrhiza, slow release fertilizer, organic fertilizer, and control. Experimental units were field plots of 12 m2 which were distributed according to a randomized block design with three replications. Seed production and germination, and forage production were estimated. In general, highest (P 0.05) seed production for all grass species was shown by 120-60-00 and 60-30-00 + mycorrhiza, where values ranged from 289 kg ha-1 in blue grama under 120-60-00 to 1,619 kg ha-1 in wilman lovegrass under 60-30-00 + mycorrhiza. Slow release fertilizer and 60-30-00 fertilizer rate showed higher seed germination percentages (P0.05) at 14.5% in blue grama, and 96.5% in green sprangletop both under slow release fertilizer. Some fertilizers increased seed yield and germination, and forage production. Keywords: seed yield, seed germination, chemical fertilizers, slow release fertilizers, organic fertilizer.

Mohammed Mustafa H.H, Ali Abdul Fattah Alshaher

The world and its various fields witnessing many changes resulting from economic, political, social and technological developments. Where the societies are racing to have as much as possible information because primary is the raw material in its success and facing to these developments. In addition to use of information technology with high intensity these communities as known as the information society. Educational institutions must be at the forefront of organizations that rely on information and information technology- for their activities.Hence, the intellectual dilemma of research which is the diagnosis of the availability of the ingredients for building an information society in the College of Administration and Economics to be considered among these communities' societies? The research focuses on achieving a fundamental goal which is to measure the availability of the components of the information society in order to be adopted in building of this society. The researchers adopted questionnaire as a tool to collect field data and then prepared for this purpose. As the form questionnaire included 34 questions. And the selected of a sample of (86) my teaching was chosen from the faculty members of the college of management and economics /the university of mosul, as for the case study method was used. The researchers reached a number amount to a number of conclusions, the most important of which is a weakness in the orientation towards the authoring and publish of scientific books by university professors. As for the most important proposals that were presented in the research are the importance of caring for providing the provision of information technology in all colleges of the University of Mosul because it is one a basic of the requirement in contemporary university education.

María Pache-Durán, María Teresa Nevado-Gil

Hoy en día, las empresas muestran un mayor interés por la aplicación de prácticas de Responsabilidad Social Empresarial con la finalidad de obtener un mayor desarrollo económico, así como mantener una buena relación con sus grupos de interés y generar bienestar social y ambiental. En este contexto, el objetivo de este estudio es evaluar la divulgación de prácticas socialmente responsables por parte de las empresas pertenecientes al IBEX35 en sus páginas web, utilizando la técnica de análisis de contenido. Los resultados revelan que la información sobre Responsabilidad Social Empresarial que ofrecen es cuantiosa, tal y como revela el índice de divulgación total, siendo la información en materia económica la más divulgada.