bluuebunny/crossref_metadata_2025 huggingface dataset:
Implicações das equipas educativas nas aprendizagens dos professores e nas práticas de sala de aula
Authors: Pinheiro Generosa Pinheiro , Matias Alves José
Published: October 2024

Nas últimas décadas, a colaboração entre os professores tem sido objeto de estudo a nível global, e a literatura tem demonstrado que a maioria dos docentes já colabora entre si e parece apresentar uma mentalidade mais colegial e colaborativa. Porém, a colaboração realiza-se numa gramática organizacional espartilhada e rígida, sendo um conceito complexo, que pode concretizar-se de diferentes formas, dependendo do contexto em que ocorre, dos seus participantes, da intensidade das diferentes interações, do seu conteúdo e objetivos. Assim, procuramos, neste estudo, compreender o tipo de interações colaborativas existente entre professores a trabalhar em equipas educativas, assim como os seus efeitos na sua aprendizagem e nas práticas de sala de aula. Nesse sentido, adotamos um paradigma de investigação tendencialmente qualitativo, que operacionalizamos através de um estudo de caso, em que conjugamos uma abordagem quali-quanti. Para analisarmos a frequência e amplitude das interações entre os professores, optamos por uma estatística descritiva, que submetemos a uma análise e interpretação estrutural e semântica. Recorremos, também, a uma abordagem qualitativa, no sentido de aprofundarmos alguns contextos singulares e a perspetiva de atores individuais: diretor; coordenadores das equipas educativas; professores; técnicas educacionais; e alunos. Feita a análise de dados, concluímos que continuam a predominar, nas equipas educativas, práticas de colaboração simples, baseadas essencialmente no intercâmbio de informação e materiais, num contexto de colaboração artificial, confortável, balcanizada, debilmente convergente e escassamente ativa, sendo, ainda, raros os momentos de coconstrução. Estas dinâmicas colaborativas podem estar a limitar uma aprendizagem profunda dos professores e a explicar a mudança ténue e lenta das práticas de sala de aula.
Ungrading’s Impact on Learning and Autonomy: Insights from an Empirical Study
Authors: Burns C. Sean , Pusateri Jennifer , DiGiacomo Daniela K , Ritchie Katherine
Published: October 2024

Library and Information Science (LIS) is an interdisciplinary field that integrates principles from various disciplines, including computer science and the humanites, positioning itself uniquely within STEM. This paper explores the adoption of ungrading in STEM-focused LIS courses and challenges grading paradigms to foster more inclusive and effective learning environments. Through a mixed-methods study involving thirteen graduate students, the research examines the impact of ungrading on student engagement, learning effectiveness, and perceptions of the learning environment. The research is ongoing, but preliminary findings suggest that ungrading reduces stress, shifts focus towards mastery, supports interest-driven learning, and promotes student responsibility for their own learning. The effects align with Universal Design for Learning (UDL) principles, suggesting that ungrading can enhance educational access and equity. This study contributes to the discourse on pedagogical innovation in LIS education and advocates for a shift towards assessment methods that emphasize learning and improvement over traditional grading schemes.
The (mis)Information World of Moms for Liberty: A Digital Ethnographic Case Study
Authors: Becker Jamie A. , Anaya Toni , Hovious Amanda
Published: October 2024

Moms for Liberty (M4L) is an American organization that has played an outsized role in the dramatic increase in book bans and challenges in school and public libraries. This group provides an opportunity to study the various ways that information and attention is driven bi-directionally between the public and private spheres. The aim of this digital ethnographic case study was to better understand how the norms and values that underlie the small world of M4L influence the larger lifeworld and social milieus of communities. If public policy is ideologically constructed, what does this mean for information practitioners whose institutions exist in small worlds? Jaeger and Burnett’s theory of information worlds and Engeström’s activity theory model were combined to form the lens of interpretation to analyze the normative behavior and information values of M4L and the impact of its object of motivation for creating information poverty in the lifeworld through censorship efforts via political activism and propaganda. Data sources included public messaging from M4L and affiliated social media pages, primary sources from M4L’s official website, official interview transcripts, news headline data, and relevant public policy data. This poster reports on the early findings and emerging implications of the study, as well as the potential value of the proposed theoretical-methodological framework for ethnographic and case study research within the information disciplines.
Redesigning for Open Educational Practices: A Faculty-Librarian Collaboration
Authors: Kammer Jenna , Evans Sara , Klein Janette
Published: October 2024

Open educational practices (OEP) are rarely explored in LIS education, despite its alignment with many of the core values in library science. Recent scholarship on LIS pedagogy does speak to the merits of OEP, which can include open and equitable access, real-world learning experiences, and principles of social justice. However, there is little discussion about what this looks like in practice and within the LIS curriculum. This thought piece examines the practical aspect of using OEP in the LIS graduate classroom and describes the collaborative reflections of an LIS faculty member, librarian, and university librarian to prepare to implement OEP at a regional comprehensive university. This collaboration found that OEP is a good fit for the library science curriculum, but that there are important support considerations which need to be secured before implementation, such as access to participatory technology, training on intellectual property and staffing. In addition, the dynamic nature of OEP addresses some of the challenges associated with the current landscape of online learning in higher education, including delivering more engaging pedagogy, increasing student digital literacy and student involvement in the scholarly communication process.
Intersecting Disciplines: Should LIS Competencies Include Social Work?
Authors: Chancellor Renate , Crooks Shannon
Published: October 2024

Social work in librarianship is a phenomenon that has gained momentum in public libraries since the first known social worker began working at the San Francisco Public Library in 2009. Few LIS programs offer courses to address this evolving phenomenon, yet librarians and library staff nationwide have expressed the need to have training in social work to help them meet the needs of their users. To date, there are only three universities (Dominican University, University of Michigan and Middle Tennessee State University) that offer dual degree programs and even fewer universities that offer social work librarianship courses. With the concern of librarians not feeling equipped to address the social needs of library users (eg. depression, anxiety, suicide, health issues, substance abuse, poverty) this paper emphasizes the critical need for LIS programs to adapt their curriculum to adequately prepare future librarians for public librarianship.
Methodological Implications for Video-Based Research in the Library and Information Science
Authors: Jung Yong Ju , Kim Soo Hyeon , Choi Gi Woong
Published: October 2024

The use of video has been popular in psychology and educational research (Erickson, 2011), but still is relatively new to the Library and Information Science (LIS) field. Video technology is a powerful tool for documenting events, allowing them to be preserved permanently and viewed un unlimited number of times for collaborative data analysis (Jordan & Henderson, 1995). In addition, it is important to consider that video recordings start with a choice of the recorder on which part to capture and follow with a deliberate and selective choice on which recordings to focus on analytically. Thus, researchers who choose to employ video-based research need to be reflexive of the affordances and limitations of using certain video technology and be cognizant of the ways in which we can be closer to capturing the phenomenon itself. In this poster, we will demonstrate two cases of family programming at public libraries where video-based research was used for research and explore the methodological implications of video-based research in LIS. We aim to discuss the opportunities and challenges of capturing in-situ data in addition to participants’ retrospective perspectives after their participation in library programming.
Understanding Information Literacy Instructional Practices: Implications for Preparing Pre-Service Librarians
Authors: Julien Heidi , Latham Don , Gross Melissa , Montiel Hernandez Jesus
Published: October 2024

The role of academic librarians in supporting people to navigate the changing information environment is fundamental to librarianship and is critical in the current information environment. This poster focuses on the implications for educating pre-service librarians about the realities and challenges associated with that role, drawn from a national survey of instructional librarians in the U.S. The project speaks directly to the conference theme, “The Ethics and Evolution of Truth and Information,” as the survey respondents engage directly on the frontline of these issues. Implications for shaping the expectations of future instructional librarians will be revealed from findings of a national online survey currently underway. The survey returns to a series of questions motivating longitudinal surveys of librarians’ instructional practices conducted in other countries, and most recently conducted in the U.S. in 2016 (Julien 1998, 2000, 2005; Julien, Gross, & Latham, 2018; Julien & Leckie, 1997; Julien, Tan, & Merillat, 2013; Polkinghorne & Julien, 2018). These data paint a detailed picture of the daily practices of these professionals and the challenges they face. Despite changing technology, introduction of the ACRL Framework (2015), and the explosion of artificial intelligence use, many of the instructional practices and the pressures associated with the instructional role have remained stable (although the recent pandemic moved instruction online, at least for a time). Developing realistic expectations for the workplace is as relevant as is developing conceptual understanding, skills, and attitudes. Thus, the survey data provide an excellent opportunity to inform the education of master’s students.
Community College Libraries and Professional Development
Authors: Aguiñaga José
Published: October 2024

The inception of this research inquiry showcases the PI’s past academic library and current LIS faculty experiences, which focuses on the need to provide continuous learning opportunities for community college library employees. With that in mind, the PI will distribute an online invitation to various lists of community college library employees to participate in this study. In this mixed-methods study. The online survey will have two portions: Likert-scale questions and open-ended inquiries to assess participants' preferences and perceptions of professional development at their respective institutions. The platform used to obtain the respondents' data will be Qualtrics. Each research method will be assessed for commonalities and differences. Any data triangulation will be presented and disclosed in a future peer-reviewed publication. Gaining a better understanding of community college library employees concerning professional development can assist current leaders and provide additional research opportunities.
How Data is Documented: An Analysis of Metadata Schemas for Research Data
Authors: Jiang Tianji
Published: October 2024

The importance of metadata has long been understood by those in the fields of librarianship and research data management. Currently, there are many research data service providers that allow deposit of research data or gather metadata for research data housed elsewhere, following various metadata schemas to describe their collections. These schemas were designed to make their datasets organized, discoverable, and reusable. As data curators initially recognize the need for and begin working on metadata schemas for research data, most previous studies in this field were conducted from their perspectives. However, few of these studies discuss a schema from the perspective of data (re)users. This study aims to take a small step towards filling this gap by evaluating four influential metadata schemas in light of researchers' information-seeking behaviors for research data. This study explores the factors that affect researchers’ efforts in seeking, understanding, and evaluating (re)usable data, and examines how these factors are represented across various fields in the current metadata schemas for research data.
The methodology for this study consists of three parts: a meta-analysis of relevant research on researcher’s seeking behaviors for (re)usable data, a crosswalk of the metadata schemas, and a comparison of findings from the previous stages. The findings from this study will offer insights into the development of research data metadata schema in the future, which will enhance the infrastructure for data sharing, ultimately facilitating more effective (re)use of existing data.
Building Information Worlds through Community and Experience: Preliminary Findings of an Ethnographic Study of Vehicle Residents’ Information Practices
Authors: Montague Kaitlin
Published: October 2024

Across the United States, an estimated one million people inhabit vehicles as their primary method of housing. While vehicles are among the most common shelters aside from brick-and-mortar homes, few studies have explored this populace. This is among the first studies that investigate vehicle residents from an information perspective. Based on six months of ethnographic fieldwork, this study seeks to explore vehicle residents’ information practices and the resources and source preferences used to support their daily lives. The end goal is to understand how information institutions, namely public libraries, can create service provisions to offer support. Through an information worlds lens, coupled with information horizon interviews, this research seeks to examine how trust is built within this community through information seeking via other vehicle residents. Preliminary findings suggest that the trust constructed within this information world directly impacts vehicle residents’ decisions to turn to their community for information.
Decoding Anti-Blackness in Children’s Literature
Authors: Kaaba Vashalice
Published: October 2024

This dissertation critically examines the representation of Black authors and themes within the John Newbery Medal canon from its inception in 1922 to 2023. It explores how this literary award has mirrored or challenged societal perceptions of race, particularly in children’s literature. Utilizing a thematic content analysis methodology, the study investigates the works of the six Black authors who have won the Newbery Medal, using a priori coding to critically examine the racial narratives, themes, and authorial diversity presented in these titles. Despite the noted increase in diversity within children’s literature, this research identifies a persistent underrepresentation of Black authors and Black cultural themes in Newbery Medal recipients. The study highlights a significant gap in racial inclusivity, with a mere six Black authors receiving the Newbery Medal in over a century. This underrepresentation is not only a marker of racial disparity but also reflects broader systemic biases within the literary and publishing industries. This dissertation engages with theories from critical race theory and critical librarianship to interrogate the structural barriers that sustain this racial homogeneity. In examining the implications of these findings, the research advocates for a more equitable literary landscape, emphasizing the need for librarians, educators, and publishers to foster inclusivity in children’s literature. The ultimate aim is to ensure that young readers encounter a more representative spectrum of narratives that celebrate racial diversity and promote inclusiveness.
Are we ready? Generative AI and the LIS curriculum
Authors: Kizhakkethil Priya , Perryman Carol
Published: October 2024

The US Department of Education’s 2023 report highlights the importance of AI literacy for educators and other stakeholders (Cardona, Rodriguez & Ishmael, 2023). Analyzing this report, Lo (2023) notes that “for librarians, AI literacy could involve understanding how AI tools work, how they can be used to enhance library services, and how to navigate potential ethical issues related to AI” (p. 2). Southworth et al (2023) observe that technical aspects of AI are covered in the traditional STEM curricula but are largely absent outside of it. While there are efforts currently to provide education and training opportunities for librarians in addressing AI in their work, as well as literature that talks about how AI will impact various aspects of work in libraries, few have touched on the need for curriculum development to effectively address such disruptive technologies by identifying the competencies or threshold concepts that will be affected by them. The ubiquitous impact of AI has included applications in medical research as well as law, design, economics, and humanities, to name just a few. Agile practice and improved dissemination of best practices are called for, moving forward. How should LIS curriculum address AI and related issues to prepare future librarians and information professionals? This poster covers an in-progress scoping review of literature and a content analysis of the publicly available course descriptions of ALA accredited LIS programs, as well as their current mission statements and objectives to provide a snapshot of extant integration of this new and challenging technology.
Where Theory and Practice Converge: Community-Based Learning as a Pedagogical Approach for Teaching AI Ethics
Authors: Trembach Stan
Published: October 2024

As artificial intelligence (AI) technologies continue to inundate the current information landscape, questions surrounding the ethics of AI and its responsible use in teaching and learning remain firmly on the forefront of the pedagogical discourse in the LIS field. Indeed, one implication of the ongoing AI revolution for LIS education that has become evident from these conversations is the pressing need to develop an ethical instructional framework that would enable students and educators alike to successfully navigate the rapidly evolving generative AI universe.
This poster discusses the effectiveness of several pedagogical approaches that are currently being implemented to help students identify and address the ethical challenges associated with these technologies across a wide range of graduate level LIS courses, spanning such key areas of the professional practice as library and information center management, academic librarianship, and community-engaged librarianship. The common denominator in these courses is an emphasis on community-based learning that constitutes the core of complex sequential semester-long course projects students are asked to complete by designing and performing various community outreach, observational, and analytical exercises in an information organization of their choice. Based on the data collected from the above-mentioned courses during the past four semesters, the presenter demonstrates the value of the community-based learning component present in these activities for developing in LIS students a higher level of critical thinking about AI-related ethical dilemmas, all the while preparing soon-to-be information professionals for real-world applications of ethical considerations in their current and future professional roles.
The Difference Between Passive Subjects and Autonomous Actors: Proposing an Orientation Toward Consent in Library and Information Science
Authors: Roeschley Ana , Merrion Dale Frederick
Published: October 2024

To participate in most aspects of society, individuals are constantly required to share their data. From students in LIS courses to patients forced to enter information into third party software to check into medical appointments, we all have to “consent” to live our lives. While we are presented with consent forms full of legalese constantly, opportunities to opt out are rare. This critical essay posits that to prepare our students to become ethical members of information professions, LIS educators must center consent as a core ethical value. Using a scoping review approach, we explore consent as a distinct topic in LIS literature. We then propose an orientation towards consent that can center human rights, individual autonomy, and care in LIS work.
Evaluating The Value and Impact of Makerspaces on Public Libraries
Authors: Koh Kyungwon , Balasubramaniam Gowri , Knox Emily , Zalot Andy
Published: October 2024

This study addresses the need to evaluate the value and impact of a public library makerspace broadly at the organizational level. Since they first appeared in U.S. libraries in 2011, once viewed as a trend or an emerging service, nowadays a number of libraries incorporate makerspaces or maker programs as part of their core, regular services. While existing literature on makerspace evaluation primarily focuses on individual learning outcomes (e.g., STEM learning), our study found the value of makerspaces to their libraries. Thirteen focus groups were conducted in three public libraries in Illinois, engaging forty-two participants including users, non-users, teens, staff members, and community stakeholders. Data unveiled that makerspaces support libraries' missions in new and expanded ways, upholding core values of librarianship; change people's perceptions of libraries and increase pride in their libraries; and attract new community members and encourage broader usage of library services.
A sociotechnical history of an AI video chatbot: Mapping AI chatbot innovation trajectory for information policy design
Authors: McGowan Catherine
Published: October 2024

This study traces the patent citation network of U.S. Patent 11,107,465 Natural Conversation Storytelling System (Gustman et al, 2021) to map the innovation trajectory of AI Chatbots. This patented AI video chatbot enables the reanimation or digital resurrection of humans in video form. As GLAMs continue to experiment with new technologies such as historical figure chatbots to increase engagement through gamification and empathy, a critical examination of technologies that are designed to appear human-like is warranted as they often skirt credibility, accuracy, and likely insert bias. Furthermore, the rise of generative AI tools and the propensity for producing hallucinations (Christensen et al, 2024) increases ethical issues for the implications on humans and truth (Ranalli, 2022; Stahl and Eke, 2024).
Patent citation network analysis is frequently conducted as a competitive strategy for mapping the trajectory of technological development and patented inventions (Érdi et al, 2013; Jain et al, 2020). Drawing from this method, innovation trajectory routes or pathways will be traced through the patent citations to identify the most prominent or critical patents in the AI video chatbot innovation trajectory and analyze which features of technical innovation are retained across its pathway. These methods are frequently utilized to understand changes, patterns, and development in innovation to predict economically viable futures and can be utilized to predict the needs for information policy (Frohmann, 1995) by understanding the implications asymmetrical power on society.
Shannon, Wiener, and the Alethic Value of Information
Authors: Mestre Juliana
Published: October 2024

This paper uses historical and deconstructive methods to examine contrasting visions of information’s alethic value. It focusses specifically on the research and legacies of Claude Shannon and Norbert Wiener, two founding fathers of information science. Shannon’s formulation of information as a statistical function of probability emphasizes a kind of pragmatism: information that can be broken into bits and transmitted through a system possesses alethic value. Wiener’s research and career set a contrasting example to that of Shannon in relation to a construction of truth. The alethic value of information in the Wienerian tradition is derived not only from its pragmatic transference within a system, but also from the way in which it interacts with other systems through feedback loops. The dichotomy set by Shannon and Wiener implicates broader questions surrounding conceptualizations of truth in LIS research today.
Toward Governance Best Practices for Open Educational Resources
Authors: Daly Diana , Schneider Nathan , Ahmad Hibah
Published: October 2024

Open educational resources (OER) constitute a form of digital media that have received growing interest and adoption. Infrastructures are becoming more widely available to support OER authorship and adaptation. However, this article argues that infrastructures for the ongoing governance of OER have been lacking, despite the medium’s possibilities as “evolutionary media.” The article provides a review of existing literature on OER and their governance, in conversation with the governance of other kinds of software commons. It then offers an auto-ethnographic reflection on the authors’ experience with the challenges of OER maintenance in the context of a specific textbook on social media, and the resulting need for taking governance seriously. Finally, the article proposes strategies for improving support for OER governance through collaborative processes among their stakeholders.
Navigating the Challenges of Legacy Data: A Systematic Literature Analysis
Authors: Stahlman Gretchen , Kouper Inna
Published: October 2024

Legacy data is data collected systematically in the past, for which contemporary use and reuse are at-risk, difficult, or impossible due to issues such as missing metadata, obsolete storage media, outdated file formats, and unsupported software. As we introduced in Buchanan, et al. (2023), there is a demonstrated need for more systematic understanding of legacy research data efforts and the value of these data and efforts as perceived across stakeholder groups. We are conducting a literature analysis of publications on the topics of legacy research data use, preservation, curation, and management. Using an established search query and online literature databases, we retrieved and manually reviewed a pool of 1,338 results and identified 69 papers that fit the following criteria for our study: peer-reviewed articles published in the last 15 years including studies discussing methodologies and best practices; studies that describe repurposing legacy data; studies focusing on storage or archival methods for older data; and studies that discuss software and migration challenges. We are analyzing the sample of papers using content analysis and bibliometric methods, focusing on references to individuals involved, processes, data types, formats, locations, and problems being addressed.
A Feasibility Study of AI-Generated Resources for K-12 Information Literacy
Authors: Yi Kwan , Turner Ralph , Syn Sue Yeon , Williams Mandy , Hardin Angela , Long Taylor
Published: October 2024

In today's rapidly evolving digital landscape, nurturing information literacy (IL) skills is paramount for lifelong learning and informed citizenship. School library programs serve as crucial catalysts in this endeavor, imparting essential IL competencies to K-12 students and fostering a community adept at accessing, evaluating, and utilizing information resources responsibly. However, the abundance of information sources complicates the task of discerning credible and relevant sources from unreliable ones. Additionally, the widespread presence of false, misleading, or outdated information presents significant challenges to educators striving to impart students with essential IL skills.
This proposal seeks to address these challenges by investigating the potential of using generative Artificial Intelligence (GenAI), specifically the ChatGPT, in the creation and dissemination of IL information for K-12 educators. Specifically, the study will evaluate resources generated by ChatGPT on digital citizenship using the template aided by Common Sense Media’s Digital Citizenship, a widely recognized and utilized resource for information literacy in K-12 education. By assessing the suitability and effectiveness of AI-generated resources, the study aims to provide insights into the potential of AI in supporting IL instruction. The results of the study can guide future development in K-12 information literacy curricula by providing and utilizing valid and reliable AI-generated resources for IL education. 
This study directly engages with the conference theme of the evolution of information by examining the potential of employing AI-generated information for K-12 information literacy education. It introduces a novel approach to both the production and consumption of information.
Information Seeking and Sharing Among LGBTQ University Students: Dynamics Within LGBTQ Communities on Social Media
Authors: Wang Shengang
Published: October 2024

In my dissertation research, I investigate the nuanced dynamics between LGBTQ university students and social media platform design, identifying the facilitators and obstacles they encounter while seeking and sharing information in online communities. This study serves a dual purpose: to explore the information-seeking and sharing experiences of LGBTQ students on social media, and to analyze platform design aspects that either enhance or hinder these information behaviors. By addressing both elements, the research aims to provide a holistic understanding of information practices within LGBTQ online communities and offer actionable recommendations to improve social media design, fostering a supportive environment for LGBTQ students.
Adopting an exploratory mixed-methods approach, I employ both qualitative methods (i.e., initial interviews, diaries, and follow-up interviews) and quantitative method (i.e., online survey questionnaires) to collect data. Integrating qualitative and quantitative methods ensures a thorough exploration of the topic, offering nuanced insights into LGBTQ students’ online experiences.
The dissertation holds both theoretical and practical significance. It advances our understanding of LGBTQ students’ information behaviors within online communities and examines the interplay between social media platform features and these behaviors. Practically, the research provides valuable insights for LGBTQ organizations, community administrators, and social media developers. By addressing the unique information needs of LGBTQ students and enhancing social media platform design, this study facilitates the creation of inclusive, supportive, and user-friendly online environments for LGBTQ individuals.
Libraries’ Environmentally Sustainable Practices and Services in Three States
Authors: Ren Xiaoai
Published: October 2024

This article reports findings from an exploratory survey study of libraries in California, Florida, and Georgia on their day-to-day environmentally sustainable practices and related services, along with the respondents’ perception of library’s role and challenges in promoting environmental sustainability. Findings from this study show that the most common environmentally sustainable practices in these libraries are Reduce, Reuse and Recycle, and energy saving practices. Many libraries have taken individual actions, such as the 3Rs, or held programs on environmental issues. However, not many libraries were considered to have established policies or systematically address environmental issues. The respondents view library’s role as primarily the information providers and educators. Lack of money, staff time and subject expertise are the top challenges faced by libraries when promoting environmental sustainability in their community followed by competing priorities on library’s plate as well as a concern that promoting environmental sustainability in their community might be viewed as a political charge. Findings from this study contribute to the understanding of library’s roles and environmental sustainability, and inform the design of future studies on this topic and provide ideas on how to better support libraries.
The Relationship Between Misinformation And Social Noise And Their Impact On The Information Ecosystem
Authors: Alsaid Manar
Published: October 2024

Social noise and social entropy are new concepts modeled after Shannon’s information and communication theory, in which the interference of noise between the sender and receiver is measured using entropy. Social noise in the context of social media plays a vital role in magnifying and spreading misinformation, which in turn impacts the overall information ecosystem. Ecosystems are made of interconnected and integrated parts that rely on one another to maintain balance and survive. Studies related to social noise and misinformation have shown that social noise can contribute significantly to spreading misinformation and potentially alter the original intended message (Alsaid & Pampapura, 2022); Alsaid et al. (2024). paper investigates methods of quantifying social noise using entropy to minimize the spread of misinformation on social media, particularly X. Using a combination of Uncertainty Reduction Theory (URT) and Social Entropy, data analysis was performed using one million tweets harvested from #Ukraine. Data analysis involved several methods: sentiment analyses, term association, network maps, and entropy computation. Results have shown a direct relationship between social noise and social entropy as a measure of uncertainty. Also, social noise and uncertainty decrease with the use of URLs and rich content. It is evident from the results that the entropy value is influenced by the accuracy of keywords identified using topic modeling as descriptive of social noise constructs. Semantic analysis of tweets can help improve the definition of social noise constructs, leading to enhanced and more accurate entropy calculation. Future studies may  consider advanced machine learning and AI
Welcome to #SpoonieTok: Understanding and supporting disability expertise storytelling abilities and collective information practices on TikTok and beyond
Authors: Lundy Morgan
Published: October 2024

This work-in-progress poster explores individual and collective storytelling and information creation practices in chronic illness TikTok communities, with the ultimate goal to support these embodied, creative, and multimodal abilities on and off-app through codesigned storytelling support materials. Findings from ongoing data collection and grounded theory coding, include folks’ sharing of disability expertise: using platform features to visualize invisible disability; audio, visual, and community-specific mimetic options. Interviews with 11 community members illuminate how disabled creators on TikTok engage in algorithmically-mediated online health communities, which have slippery boundaries where information can be found serendipitously through algorithmic ranking, and foster opportunities to develop storytelling skills.
Information Privilege: Considerations for Library and Information Science Curriculum Design
Authors: Ahmed Abass , Agosto Denise
Published: October 2024

Embedded within the ACRL Framework for Information Literacy for Higher Education and building on the broader concepts of privilege and oppression, information privilege (IP) might be a useful lens for centering library and information science (LIS) curricula on information-related aspects of social power. IP suggests that individuals' access to and utilization of information is connected to demographic factors like socioeconomic status, place of birth, and gender. Despite the relevance of this concept to LIS scholarship and teaching, LIS scholarly discussions on information privilege are limited. The limited existing literature mainly extends Booth’s foundational essay exploring IP through the lens of institutional affiliation, stopping short of fuller sociocultural considerations. This essay considers IP as an information-focused organizing perspective within LIS teaching and curriculum development. The authors conclude with suggestions for building discussions of IP into LIS curriculum and teaching.
DETECTION OF BLACK HOLE ATTACK USING CROSS LAYER CONCEPT IN MANET
Authors:   Dhar Polytechnic College, India, Karma Shyam Sundar
Published: October 2024

Mobile Nodes can communicate mutually if it falls in the sensing range of the neighboring nodes. Connected nodes can transmit, receive and forward packets to connected nodes. In this paper, we focus on detection of Black Hole attack in the MANET using the cross-layer techniques that can optimize the energy consumption. The proposed cross-layer framework contains three layers and uses parameters like mobile nodes, area and the data in network layer. The MAC and data-link layer is used as a sub-layer, and a full-duplex interface is developed through the physical (PHY) layer. Our focus here is make a secure mechanism particularly to counter Black Hole Attacks through cross-layer proposal. The proposed framework is simulated using NS-3 version NS-3.17. Our examination observes the correlation between Cross Layer and Black Hole Cross-Layer scenario. This correlation is noticed between the simulation time and mobile nodes in view of the QoS parameter like execution time, redundancy gain, average end to end delay, average throughput, and network reliability. A redundancy gain performing 100% in Cross Layer with respect to Black Hole Cross Layer, thus increases the performance of the network. The simulation results show that Cross Layer approach and detection of Black Hole in Cross Layer Network is better than Black Hole Cross Layer.
A GENETIC ALGORITHM BASED LEACH PROTOCOL FOR CLUSTER HEAD SELECTION TO ENHANCE THE NETWORK LIFETIME OF WIRELESS SENSOR NETWORK
Authors:   Sant Longowal Institute of Engineering and Technology, India, Kumari Manisha , Kaur Gurjinder ,   Sant Longowal Institute of Engineering and Technology, India
Published: October 2024

Increased interest in the usage and deployment of Wireless Sensor Networks (WSN) has resulted in the development of a slew of novel routing protocols, all of which place a premium on energy efficiency. The most challenging aspect of wireless sensor network is surviving for an extended period using energy efficiently. To make the network last longer, the protocols must be energy efficient. In Low Energy Adaptive Clustering Hierarchy (LEACH) protocol, Cluster Head (CH) selection is based on a random probability equation, and has limitations such as unequal distribution of clusters and energy, and random selection of CH. In order to solve these limitations, a method is proposed for improving CH selection and reducing CH energy degradation. The proposed algorithm, LEACH-CHGA protocol strengthens CH selection compared to the existing protocol while simultaneously lowering network energy usage. The optimal CH selection based on a genetic algorithm enhances network lifetime and energy consumption as compare to LEACH.
MICROSTRIP LINE-FED BASED QUAD-PORT WIDEBAND MIMO ANTENNA FOR K BAND APPLICATION
Authors:   University of Allahabad, India, Pandey Amrees , J A Ansari ,   University of Allahabad, India, Masroor Iqra ,   University of Allahabad, India, Mishra Piyush Kr ,   University of Allahabad, India
Published: October 2024

In this communication, a compact (30×30×1.6 mm3) microstrip line fed loaded quad-port and T-shaped wideband MIMO (Multiple-Input Multiple-Output) antenna for K band (18-27GHz) application is introduced. Here three simulated antennas (Antenna-1, Antenna-2 and Antenna-3) are analytically inspected in expressions of simulated gain, return loss (|S11|, |S22|, |S33| and |S44|), total active reflection coefficient (TARC), isolation (mutual coupling), diversity gain (DG), radiation efficiency, radiation pattern and envelope correlation coefficient (ECC). Antenna 3 disclaimers have been elevated for chosen antenna considerations and performance. The proposed antenna has |S11|, |S22|, |S33| and |S44| not more than -10 dB and the percentage impedance bandwidth is 19.54% (19.48-23.70GHz), 18.74% (19.58-23.63), 16.31% (19.54-23.01GHz) and 18.27% (19.39-23.29GHz) at ports 1, 2, 3 and 4 respectively. Simulated isolation is < -15 dB, ECC obtained between ports 1-2, 1-3 and 1-4 is not more than 0.06, DG originated among the ports 1-2, 1-3 and 1-4 is in the range of 9.969-9.999 (dB), TARC < 0 dB and radiation efficiency of 60% is obtained. The proposed design model of antenna has been analyzed with HFSS simulation tool by ANSOFT version 13.
A CASE STUDY OF ELECTROMAGNETIC EXPOSURE FOR HIGH TENSION POWER LINES AND TRANSFORMER WITH AND WITHOUT BASE STATION ANTENNA
Authors:   Maulana Abul Kalam Azad University of Technology, India, Roy Kousik , Dey Pratik ,   Maulana Abul Kalam Azad University of Technology, India, Hasan Naimul ,   Maulana Abul Kalam Azad University of Technology, India, Parui Susanta Kumar ,   Indian Institute of Engineering Science and Technology, India
Published: October 2024

With the fast growth of electric activity and the spreading out of town scale, our lives are approached by extremely high voltage power transmission lines. And with the expansion of ultra-high voltage power transmission line, the ultra-high voltage transformer substation will come out in the place with intense inhabitants and the electromagnetic exposure of this transmission and transformer apparatus and its contamination to the inhabitants stimulate the immense anxiety from the civilization. This paper deals with electromagnetic radiation of extremely high voltage power transmission line. Here we have observed the electric and magnetic field beneath the transmission line by the process of equivalent charges and put forward the anticipation rule to the electromagnetic radiation in the engineering of extremely high voltage power dissemination and remodeling. Recognition the safe distance from the EMF produced from the high-tension overhead power lines in the locality of the precise region is the detailed goal of this study. The high-tension transmission lines generated EMF that bounded the projected site has to be underneath 0.2 µT. The safety approval distance has been allotted as 200 m from the active 300-KV high-tension power line.
ANALYSIS OF BRAIN SUB REGIONS USING OPTIMIZATION TECHNIQUES IN ALZHEIMERS DISEASE
Authors:   R.M.D Engineering College, India, R Aarthi , K Helenprabha ,   R.M.D Engineering College, India
Published: October 2024

AD is a progressive neurodegenerative disorder impacting specific brain sub-regions. Accurate identification and analysis of these regions are crucial for early diagnosis and effective intervention. This study employs optimization techniques to enhance the understanding of AD-related alterations in brain sub-regions. Utilizing medical imaging data, a multi-step approach is implemented. Image segmentation algorithms optimize brain sub-region delineation, while feature selection techniques enhance discriminative information extraction. Machine learning models, fine-tuned through optimization, classify images into AD and non-AD categories. Functional connectivity patterns between sub-regions are explored using network optimization methods. Predictive modeling and treatment planning incorporate optimization for improved accuracy and personalized strategies. This research contributes a comprehensive framework for analyzing AD-affected brain sub-regions, integrating optimization techniques into various stages of analysis. The proposed approach enhances diagnostic accuracy, provides insights into disease mechanisms, and facilitates personalized treatment strategies. The optimized methods demonstrate superior accuracy in image segmentation, classification, and predictive modeling. Connectivity analysis reveals significant alterations, offering novel insights. Personalized treatment plans, optimized for individual patients, show promise in improving therapeutic outcomes.
CLASSIFICATION OF SOCIAL MEDIA CONTENT AND IMPROVED COMMUNITY DETECTION (C&CD) USING VGGNET LEARNING AND ANALYTICS
Authors:   MIT Academy of Engineering, India, Puranik Vishal Gangadhar , V Saravanan ,   Johns Hopkins University, United States of America, P Selvaraju ,   Excel Engineering College, India, R Janaki ,   Roever Engineering College, India
Published: October 2024

Social media platforms generate vast amounts of data, necessitating efficient content classification and community detection methods. This study addresses this challenge through the utilization of VGGNet analytics, a powerful deep learning architecture. We employed a two-step approach, beginning with VGGNet-based content classification to categorize social media posts. Subsequently, a community detection algorithm was applied to identify distinct user groups based on their interactions and content preferences. This research contributes an novel framework that seamlessly integrates VGGNet for content analysis and community detection, enhancing the understanding of user behavior in social media platforms. The proposed method aims to provide more accurate and insightful results compared to traditional approaches. Our experiments on diverse social media datasets demonstrate the effectiveness of the VGGNet-based approach. The content classification accurately assigns posts to relevant categories, while the community detection algorithm identifies cohesive user groups. The results highlight the potential for improved content recommendation systems and targeted marketing strategies.
EARLY DIAGNOSIS OF ALZHEIMER’S DISEASE WITH GENERATIVE ADVERSARIAL NETWORKS
Authors:   Muslim Arts College, India, G.P. Suja , P Raajan ,   Muslim Arts College, India
Published: October 2024

Alzheimer’s disease (AD) early diagnosis plays a pivotal role in effective intervention and patient care. With limited and noisy medical imaging datasets, GANs are utilized to generate synthetic brain images, aiding in the augmentation of existing data. The selected classification algorithms are well-established in computer vision and have demonstrated efficacy in image classification tasks. The GAN is employed for data augmentation, creating synthetic images representative of AD-associated features. Subsequently, the augmented dataset is utilized to train and evaluate the performance of multiple classification algorithms, providing a comprehensive analysis of their effectiveness in AD detection. This research contributes to the field of Alzheimer’s disease diagnosis by integrating GANs for data augmentation and evaluating the performance of ten diverse classification algorithms, offering insights into their suitability for early detection. In this study, we leverage Generative Adversarial Networks (GANs) for data augmentation in medical imaging, enhancing the quality and diversity of brain images associated with AD. Various classification algorithms, including AlexNet, GoogleNet, VGG 16, VGG 19, ResNet 18, ResNet 50, ResNet 101, ShuffleNet, MobileNet, and DenseNet 201, are employed for robust AD detection. Our experiments demonstrate improved classification accuracy and robustness due to GAN-based data augmentation. Among the classification algorithms, ResNet 50 and DenseNet 201 exhibit superior performance, showcasing their potential in accurate and reliable early AD diagnosis.