This study aims to investigate college students' security awareness of using social media in sharing information. The two theories that have guided this study are the theory of planned behavior (TPB) and the technology acceptance model (TAM). Data was collected from both undergraduate and graduate students from the University of North Texas (UNT) in Denton. The total responses included 380 students from different majors with 291 valid responses for data analysis; The structural equation model (SEM) Lavaan package was used to find out the best fit of the model. A diagonally weighted least squares (DWLS) was used to model the variables as ordinal in this study's analysis as ordinal data made the model fit substantially. The study found that 6 factors: attitude (AB), subjective norm (SN), perceived behavior control (PBC), perceived usefulness (PU), perceived risks (PR), and security awareness (SA) influenced behavior intention (BI). Also, I found that AB was influenced by PR and SA, as well as SN influenced by SA. Self-efficacy (SE) influenced PBC. On the other hand, the study found that controllability (C) did not influence PBC; perhaps, an individual's skills do not interact with social media security settings. Perceived ease of use (PEOU) did not influence …

When it comes to hospice care, patients and their families residing in rural counties need competent rural community-based hospice social workers on their team. The study of information seeking behaviors of rural community-based hospice social workers during the global COVID-19 pandemic is significant as there is a need to fill gaps regarding how this specific medical discipline performs their job responsibilities when duties become more complicated due to evolving infection control protocols, decreased direct access to patients, and poor internet services. Community-based rural hospice social workers rely on up-to-date information and resources when providing support services to patients and their families. This has become particularly important during the global pandemic COVID-19. Utilizing Chatman's small world theory, this research lends itself to community-based hospice social workers identifying solutions to the challenges of finding timely and accurate COVID-19 information and resources for hospice patients and their families. Purposive sampling, semi-structured interviews, and qualitative social network analysis (SNA) with ATLAS.ti comprise the methodology for this research. The purpose of this study is to investigate the information seeking behaviors of community-based hospice rural social workers in order to understand how they select their COVID-19 information resources.

Indigenous communities around the world are losing their languages at accelerating rates to the effects of the climate crisis and global capitalism. To preserve samples of these languages facing endangerment and extinction, samples of language use (e.g., audio-video recordings, photographs, textual transcriptions, translations, and analyses) are created and stored in language archives: repositories intended to provide long-term preservation of and access to language materials. In recent years, archives of all kinds are considering their origins and audiences. With the emergence of the community paradigm of archiving framework, the roles of archivists, communities, and institutions are under re-examination. Language archives too are reflecting this trend, as it becomes more common for speakers of Indigenous languages (also known as language communities) to document and archive their own languages and histories. As the landscape of language archiving expands, we now see increased emphasis on the re-use of archival material, particularly to support language revitalization—efforts to increase and maintain the use of the language. There are calls for language documentation (and, by extension, language archiving) to prioritize revitalization efforts. This dissertation is a case study of one language archive collection: the Boro Language Resource in the Computational Resource for South Asian Languages (CoRSAL) archive. …

Relevance is a core concept in the field of Information Science and a common term in everyday vernacular that generally refers to the usefulness of information. However, relevance has not been sufficiently or consistently defined or explored in the information science literature. Relevance criteria are the factors that information users employ when determining whether information they encounter is relevant. Identifying relevance criteria is a crucial step to understanding relevance. Relevance criteria employed with newer information formats like online video are especially important to study. Online video is now widespread, and people are increasingly likely to rely on video for information. This study identifies relevance criteria employed during relevance assessments of online video through a explanatory sequential mixed-methods study of frequent online video users including students, faculty, librarians, and video professionals. Methods included an online survey and interviews.

Accurately predicting the deck condition rating of a bridge is crucial for effective maintenance and repair planning. Despite significant research efforts to develop deterioration models, a nationwide model has not been developed. This study aims to identify an appropriate machine learning (ML) algorithm that can accurately predict the deck condition ratings of the nation's bridges. To achieve this, the study collected big bridge data (BBD), which includes NBI, traffic, climate, and hazard data gathered using geospatial information science (GIS) and remote sensing techniques. Two sets of data were collected: a BBD for a single year of 2020 and a historical BBD covering a five-year period from 2016 to 2020. Three ML algorithms, including random forest, eXtreme Gradient Boosting (XGBoost), and Artificial Neural Network (ANN), were trained using 319,404 and 1,246,261 bridge decks in the BBD and the historical BBD, respectively. Results showed that the use of historical BBD significantly improved the performance of the models compared to BBD. Additionally, random forest and XGBoost, trained using the historical BBD, demonstrated higher overall accuracies and average F1 scores than the ANN model. Specifically, the random forest and XGBoost models achieved overall accuracies of 83.4% and 79.4%, respectively, and average F1 scores of …

Technological advances such as mobile technology, big data, and machine learning allow businesses to associate advertisements with consumer behaviors to maximize sales. Thus, information about consumer behavior became the central resource of businesses. Recent discussions and concerns about the emerging economic order centered around capturing consumers' data suggest that more research efforts be allocated to address new challenges in different domains, such as health, education, smart cities, and communication. Research on individual cybersecurity behavior is relatively new and requires more attention in academic research. This study has proposed and validated a cybersecurity behavioral model to enrich our understanding of users' behavioral intention (BI) to use cybersecurity controls. An online survey was used to collect information from University of North Texas (UNT) students to explore various technology usage determinants and specific computer security practices. The instrument measured the actual cybersecurity controls behaviors (ACB) by incorporating technical and social factors. Accordingly, the construct of ACB was created and validated to test how it relates to the participants' behavioral intentions. The findings confirm a large number of the proposed relationships. Additionally, the results show that the model explained a significant amount of variance in the proposed dependent variables BI and ACB. Within the …

School librarians create an atmosphere where learners feel empowered. Moreover, school library programming should support diversity, equity, and inclusive learning opportunities to facilitate student success. Thus, school librarians are expected to model and advocate for equitable learning spaces while considering the universal design for learning approach to improving accessibility, utilization, and relevance for all library patrons. Although it has been established that school library standards support diversity, equity, and inclusion (DEI), more is needed to know about the impact of a crisis on school library programming and services. In addition, extensive research has not been conducted to determine school librarians' responsiveness and strategies to provide services for their school communities during disruptive times. This study examines school librarians' perceptions of the opportunities and challenges encountered while endeavoring to engage in DEI practices during crises.

This study identified the information seeking behavior and networking practices used by members of a specific marginalized population, that of adult female probationers (AFPs) in a rural county in Texas. The study focused on how they seek out information when faced with a self-identified need in their lives. Beyond the basic "food, shelter and clothing" that comes to mind, the respondents find themselves faced with questions not only about the judicial system but also ones involving health care, employment, transportation, child-care, and other. The study utilized a qualitative research approach to gather data about the AFPs' information behavior and networking activities. The AFPs were asked about their information behavior during their time in the judicial system and after that involvement ended, and about their use of three points of information access: personal social network, physical resources, and electronic resources. Data was also gathered from community members (CMs) who have a role either within the judicial system or external to the judicial system. In its findings, the study determined there is no single point of access to a comprehensive listing of resources for the AFPs to utilize, and that AFPs reported seeking information via two ways as based on the type …

Artificial intelligence (AI) and predictive modeling are tools used to diagnose a disease, determine how much a home is worth, estimate insurance risks, and detect fraud. AI and predictive modeling are so ubiquitous that they can be why one gets spam and why spam is automatically deleted. Information science integrates interdisciplinary elements of data-driven, behavioral, design, interpretive, and analytical research methodologies to design and understand interactions between digital media, information systems, and humans. This research focuses on the interaction between humans, AI, and predictive models. This research proposes a theoretical framework and a conceptual research model to understand the antecedents to reliance on AI and predictive modeling. The dissertation follows a traditional format that includes three studies. Study 1 employed a deductive quantitative research approach as a survey to model the relationship between trust in science and reliance on formal news sources. Study 2 employed a deductive quantitative research approach as a survey to understand the impact of framing questions and consider an alternative method of measuring society's reliance on science using predictive models. Study 3 employed a deductive quantitative research approach in the form of a survey to posit a new model based on the first two studies. This …

Enterprises have focused on mechanisms to track insiders who may intentionally exceed and misuse their authorized access. However, there is an opportunity to understand why a trusted individual would want to exploit the trust and seek information with the intent of a malicious outcome. The detection of insider rogue or nefarious activities with information to which a user is already authorized is extremely difficult. Such insider threats require more deliberation than just considering it to be a problem that can be mitigated only by software or hardware enhancements. This research expects to help gain an early understanding of antecedents to such information behavior and provide an opportunity to develop approaches to address relevant character traits which could lead to a higher propensity of information misuse. This research proposes a theoretical framework and a conceptual research model to understand the antecedent factors to opportunistic information-seeking behavior of individuals. The study follows the three-essay format. Essay 1 explores the scholarly literature published about insider behavior to understand information behavior and proposes the theoretical framework for the study. PRISMA methodology was used for the thematic literature review. Essay 2 is a quantitative study of 424 university students surveyed using an online instrument for …

When the need arises to transmute complex and theoretical ideas into practice or communicate them to the uninitiated, there often exists a gap in the levels of understanding between the parties involved. This research examined knowledge transfer between practitioners within the information technology (IT) domain of interest by asking the following questions: what is the relationship between knowledge spaces for IT experts and novices; and what factors impact knowledge transfer among knowledge spaces for IT experts and novices? This study conducted interviews with a range of IT professionals to identify knowledge states that resulted in knowledge spaces for both experts and novice practitioners. A conceptual model was developed to examine the knowledge transfer process between expert and novice practitioners and identify factors affecting both the knowledge space and the knowledge states. The model also takes in consideration external factors such as organization and culture and organizational environment. The results from the study show that leadership and executive skillsets play a major role in characterizing the expert knowledge state. The results also show that knowledge transfer between and among groups was primarily impacted by interest and awareness factors among experts. Among novices, the largest barriers were cultural in nature (e.g., no …