The research examines the relationship between cyber addiction (excessive use of the Internet, CA), information overload (IO), and assesses their impact on workplace productivity. A multi-methods approach is used employing the Internet Addiction Test (IAT) and a quantitative survey design to assess and test the stated hypothesis. The study used random sampling methods targeting 150 respondents from different information technology departments of various organizations. The study hypothesizes that CA and IO have a reciprocal association, which adversely affects workplace productivity and employee performance. From the findings, IAT scores increase with an associated possibility of reporting burnout, fatigue, and other components associated with CA and IO. Also, CA and IO were significantly correlated, as evaluated by the chi-square test, although the same approach did not yield significant associations between CA and perceived internet dependence. Other findings CA components, such as social media use, significantly associated with task postponement and burnout. As well, CA affected IO with substantial impacts on workplace productivity. The paper highlights managerial aspects that organizations should consider in optimizing the output of their staff. Recommendations include wellness programs, altering the leadership and management styles, and sensitizing the employees on the adverse effects caused by the two variables.

The current research examines the use of social media and its security settings using the Social Exchange Theory (SET) within a Saudi student environment. This research includes an introduction, literature review, methodology, results, and conclusion with the results section presenting the findings from the three essays. The first essay employs the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology of SET. PRISMA's systematic and exhaustive approach to literature evaluation increases the likelihood of obtaining high-quality, reproducible findings. In the second essay, which focuses on awareness of X's (Twitter) security settings, a quantitative research approach was utilized. A sample of former and current Saudi students (graduate and undergraduate) at the University of North Texas participated in the investigation. This research provides an empirical examination of the use of X (Twitter) and its security features within this community by employing statistical analysis of the data from respondents. Likewise, the same sample of Saudi students from the University of North Texas was used for the third essay in which the use of Facebook's security settings was examined. Having a consistent sample across both studies enables a comparison and a greater understanding of the security awareness and practices of this group across …

Social media is considered a particularly conducive arena for hate speech. Counter speech, which is a "direct response that counters hate speech" is a remedy to address hate speech. Unlike content moderation, counter speech does not interfere with the principle of free and open public spaces for debate. This dissertation focuses on the (a) automatic detection and (b) analyses of the effectiveness of counter speech and its fine-grained strategies in user-generated web content. The first goal is to identify counter speech. We create a corpus with 6,846 instances through crowdsourcing. We specifically investigate the role of conversational context in the annotation and detection of counter speech. The second goal is to assess and predict conversational outcomes of counter speech. We propose a new metric to measure conversation incivility based on the number of uncivil and civil comments as well as the unique authors involved in the discourse. We then use the metric to evaluate the outcomes of replies to hate speech. The third goal is to establish a fine-grained taxonomy of counter speech. We present a theoretically grounded taxonomy that differentiates counter speech addressing the author of hate speech from addressing the content. We further compare the conversational outcomes of …

The traditional definition of tourism has been transformed by significant advancements in communication and information technology. The concept of Metaverse, derived from the words "meta" (meaning beyond) and "verse" (meaning universe), has redefined how people experience travel. This innovative concept combines virtual reality, augmented reality, and artificial intelligence to create virtually augmented spaces. However, the tourism industry should clarify and narrow down the definition of Metaverse and its intriguing concept for its successful adoption in the future. Thus, it is crucial to define Metaverse tourism and understand how users will accept it in the near future. This study aims to comprehend the technology behind Metaverse tourism, review current research on the topic, and identify the critical factors related to experiential Metaverse tourism. The paper also examines how computer self-efficacy, novelty seeking, subjective norm, job relevance, perceived usefulness, perceived ease of use, and perceived enjoyment can influence expected user satisfaction and behavioral intention, given the context of situational motivation. The findings have significant implications for theory and management, addressing various questions related to users' perceptions, expectations, design considerations, stakeholder preparations, and performance assessment of metaverse technology in tourism applications.

This dissertation examines the impact of trauma on information-seeking behaviors and decision-making processes. Essay 1 includes a qualitative analysis of the transcripts obtained from interviews with four military service members diagnosed with PTSD. The results showed that 75% of this small sample population exhibited addictive behavior that was presented in their information behaviors. All four members indicated that the excessive extent to which they seek information is related to the perceived importance of the information and their level of trust in the sources. Low trust in information sources increases the number of sources searched for validation in this population. Essay 2 involved the collection and analysis of survey data. The results of the stepwise backward regression show that two trauma variables (adult sexual assault, sudden fear) have a significant combined negative effect on decision-making in this population. The analysis and results of a different survey are presented in Essay 3. The stepwise logistic regression analysis results conducted on the summated scales developed showed a strong positive link between trust in scientific experts for scientific information and the dichotomous dependent variable trust in social media for news. The research conducted in this dissertation extends the understanding of how trauma affects people's …

This study's first goal is to investigate whether a 23-item multidimensional scale is a valid and reliable measure of benefits private club members perceive to be important. Seven theoretically plausible model structures are empirically tested: a unidimensional model, a two oblique first-order factors model, a four oblique first-order factors model, a two oblique second-order factors model, a bifactor model with two domain-specific factors, a bifactor model with four domain-specific factors, and two oblique bifactor models. The second goal is to examine the benefits members receive most often from their membership clubs. The multidimensional scale is based on four dimensions: member-to-employee relationship, member-to-member relationship, confidence, and reduced anxiety. Member-to-employee relationship and member-to-member relationship subscales are aligned with social benefits while confidence and reduced anxiety subscales are aligned with psychological benefits. The study participants (N = 114) were recruited through a commercial crowdsourcing platform, Prolific. The results of a Bayesian confirmatory factor analysis (BCFA) provided support for the two oblique bifactor models. Additionally, the social benefits and psychological benefits bifactor scales displayed acceptable reliability. A comparison of the means for each type of benefit revealed that no statistically significant differences existed between the general social benefits factor and the general psychological benefits …

This study aims to find out the impact of the credibility and content quality of social media influencers on the various stages of the customer's journey and the intention to choose a destination for the Saudi tourist. The target segment was Saudis in general, who are 18 years or above. To conduct this study, 618 usable questionnaires were collected. This study tested twenty-two hypotheses. The result of this study showed that the relationship between content quality, expertise, and similarity was significantly positive with the tourist's desire and information searching. As well, the relationship between the tourist's desire and information searching was significantly positive with the intention of choosing a destination. Conservatism, engagement, and gender were tested as moderators. Conservatism was not significant while the engagement was significant. Gender was only significant in the relationship between content quality and the tourist's desire. This study contributes to information and knowledge in the fields of tourism, hospitality, travel, marketing, tourist behavior, information science, and social media. Researchers and those interested in tourist and customer behavior can benefit from the results of this study. In the industrial field, this study will be very useful to the Saudi government, which has recently begun to rely …

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 …

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. …

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 …

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 …

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.

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.

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 …

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 …

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 …

This study explored issues related to the adoption and implementation of electronic health record (EHR) systems including building the awareness, knowledge, and experience of physicians toward cyber hygiene. This study used a qualitative research method to assess (a) the barriers to EHR systems adoption and implementation in Kuwait and (b) the level of awareness, knowledge and experiences related to cyber hygiene practices in Kuwait. The findings of the study supported the conceptual framework used to guide the research of the factors impacting the adoption and implementation of EHR systems in Kuwait as well as explore the level of awareness, knowledge, and experience of physicians about both EHR systems and cyber hygiene. The results from the systematic literature review analysis identified seven major barriers. These are financial barriers, time, difficulty of using technology, lack of support, negative attitude, legal and ethical (policies), and cultural barriers. The findings from the semistructured interviews supported the literature findings and provided more in-depth insights into the structural and social issues affecting the adoption and implementation of EHR systems. Given that Kuwait is a member of the Gulf Cooperation Countries (GCC), the results from the literature analysis showed that the problems in Kuwait are similar to …

In this study we explore the factors impacting physician patient interaction time and how these factors can be used to improve health knowledge transfer from physicians to patients. We also investigate how technology tools can be used to improve this interaction time. Physician patient interaction time is important because this is the time when both sides engage with each other, exchange information so that physicians understand their patients' health issues. Given the increasing health care costs and demand for physician time, over the years, this interaction time has been distracted due to many factors. It is important to explore these factors and provide some possible solutions, such as advanced knowledge management systems, such as knowledge portals. To identify the factors impacting this interaction time and the role of technology, we first identified the variables and then developed hypotheses. We used data from the surveys administered by the AHRQ and NCHS to test these hypotheses. We conducted correlation analyses to determine the factors that can be used to improve health knowledge transfer from physicians to patients and how technology tools can be used to improve physician patient interaction time. Our analyses indicate that the factors we identified to improve health knowledge …

The purpose of this study was to assess visual analytics technology acceptance and user experience among in vitro fertilization (IVF) consumers. The research aimed to show how visual analytics tools and technologies can be applied in the consumer space to enhance how users interpret healthcare success rate data. This exploratory user evaluation study utilized a quantitative dominant, mixed-methods approach with a convergent parallel design based on the data-validation variant. Survey data were collected from consumers who were currently seeking information about IVF treatment in the United States. The study findings indicated that the extended unified theory of acceptance and use of technology (UTAUT2) constructs of performance expectancy and hedonic motivation influenced consumer behavioral intention to use visual analytics technology, while effort expectancy did not. Further, the findings from the user experience and qualitative analyses indicated that there is strong support for consumer adoption of visual analytics technology for personal healthcare decision-making. These findings may help in the design and development of modern, interactive visualization tools that could be used to visualize public or private healthcare data for analysis by consumers. Stakeholders, including the US Centers for Disease Control and Prevention, the World Health Organization, and medical practitioners, may use the …

This study aims to apply user reviews and numerical ratings toward items to create an aspect-aware high-order representation for a recommendation system. We propose a novel aspect-aware knowledge graph recommendation model (AKGR) with the deep learning method to predict users' ratings on non-interacted items, from which more personalized recommendations can be made. First, we create a sequence-to-sequence encoder and decoder model by exploiting contextual and syntactic information in user reviews to extract aspects critical to items. Then we utilize the principal component analysis (PCA) and the K-means clustering to analyze the extracted aspects for category classification. Based on the aspects, we construct a graph structure to connect users and items which share the same aspect-based opinions for mining user preferences and item attributes. Finally, we combine the user and item latent features from the reviews and the user-item rating matrix to complete the rating prediction task by applying the factorization machine model. We conducted experiments on three aspect extraction datasets and five rating prediction datasets. To verify the effectiveness of the proposed aspect extraction model and rating prediction model, comparison experiments were made with some state-of-the-art baseline models, such as double embeddings convolutional neural network (DE-CNN) and dual graph convolutional …

This study examines the background and qualifications of plaintiff and defense experts using the H-Index score as quantification of expert background and qualifications. The goal is to better understand the similarities and differences among the professionals offering paid expert witness testimony in mild traumatic brain injury (mTBI) civil litigation. In this quantitative study, descriptive statistics include the mean and standard deviation scores for the data to support examining measures of central tendency and variance, respectively. The study includes the use of logistic regression and the Wilcoxon signed-rank test, and their statistical assumptions were tested to determine whether they would be used or if it was more appropriate to use a non-parametric test. The study included two research questions: How do the qualifications of plaintiff and defense expert witnesses in mild traumatic brain injury civil litigation compare? and to what extent does a higher h-index correlate with a favorable litigation outcome in a mild traumatic brain injury case? The findings for the hypothesis tests associated with the research questions led to the acceptance of the null hypothesis in each test. There was a lack of asymptotic significance in Hypothesis 1 and a lack of significance in Hypothesis 2. The findings from …

This study explores information seeking behavior of second-generation Muslim immigrants utilizing factors such as critical, cultural, and religious literacy skills. The study examined the second-generation immigrants' ability to balance their parents' and grandparents' native culture and traditions with the culture and traditions of their country. The interview questions were designed using the cognitive authority theory and the figured worlds theory that provides an explanation for the mentality of those who are in environments influenced by culture or religion. An interesting main finding of the study is that participants sought more religious-based rather than culturally-based information. Participants seek information from their parents, communities, and religious leaders, but are particular with who they consider credible and reliable; if the person providing the information follows a similar lifestyle to the participants, they are more likely to hold cognitive authority. Four different themes emerged from the study. The first is "religious focus" where many participants stated that religion is rather static whereas culture can evolve and change with time, location, and events. The second theme emerged is the reliance on family members for religious literacy given the close upbringing of Muslim extended family system. The third theme indicated that although information seeking behavior relied …