Miracle-dz/UniFAR-FTUs huggingface dataset:
Preliminary Findings on Developing a Scale for Credibility Assessment on Interactive Web Platforms

This poster introduces an ongoing project to develop a scale for measuring information credibility on current and newly emerging interactive web platforms. The poster reports on preliminary findings from an initial phase in the project to generate an item pool based on an analysis of existing scales for credibility (n = 3) and empirical studies in the library and information science literature on web credibility assessments in the social media context (n = 19). Results show that in most papers analyzed (16 of 19; 84.2%), credibility was conceptualized as a one‐dimensional construct and often measured with only one item (e.g., credible, believable), despite the common view among scholars that credibility is a high‐level, multifaceted concept. The analysis also identified 59 semantically distinct items as an initial pool, which will be validated and tested with empirical data in subsequent project phases.
Hyper‐Local Fear of Crime: Identifying Linguistic Cues of Fear in Crime Talk on Reddit

The fear of crime is an emotional response individuals have toward crime or the anticipation related to being the victim of crime. The increasing exposure to crime information presents considerable risks to people's psychological health and well‐being. Nevertheless, the fear of crime in online discourses is under‐researched despite abundant conversations about crime. This work presents a mixed‐methods study to comprehend how people disclose the fear of crime and what linguistic content or cues are associated with the fear. We gathered conversations about crime in the Baltimore subreddit. The content analysis revealed a necessity to differentiate between “experienced” and “expressive” fear of crime. The regression modeling identified strong factors related to the fear of crime, such as negative sentiment, objective expression, and first‐person pronouns. This work extends the conceptualization of the fear of crime in online discourses and suggests potential ways to detect the fear automatically.
Using Explainable AI to Understand Team Formation and Team Impact

The citation of scientific papers is considered a simple and direct indicator of papers' impact. This paper predicts papers' citations through team‐related variables, team composition, and team structure. Team composition includes team size, male/female dominance, academia/industry collaboration, unique race number, and unique country number. Team structures are made up of team power level and team power hierarchy. Team members' previous citation number, H‐index, previous collaborators, career age, and previous paper numbers are a proxy of team power. We calculated the mean value and Gini coefficient to represent team power level (the collective team capability) and team power hierarchy (the vertical difference of power distribution within a team). Taking 1,675,035 CS teams in the DBLP dataset, we trained the XGBoost model to predict high/low citation. Our model has reached 0.71 in AUC and 70.45% in accuracy rate. Utilizing Explainable AI method SHAP to evaluate features' relative importance in predicting team citation categories, we found that team structure plays a more critical role than team composition in predicting team citation. High team power level, flat team power structure, diverse race background, large team, collaboration with industry, and male‐dominated teams can bring higher team citations. Our project can provide insights into how to form the best scientific teams and maximize team impact from team composition and team structure.
Social VR: A Promising Platform for Enhancing Mental Wellness among College Students

In recent decades, there has been an alarming increase in the number of university and college students struggling with intensifying psychological distress, which has become a mental health crisis on campuses. To address this issue, this study proposes social VR as a potential platform to promote social interaction and improve mental well‐ being for college students. In this study, 68 students explored a variety of social VR applications in a classroom setting. Results showed that a) virtual space, audio, avatar, communication types, and activities were key contributing features that facilitated social interaction among college students in social VR and have the potential to enhance mental wellness, and b) the anonymous nature, communicative cues, and designated private areas provided by social VR platforms were effective in facilitating self‐disclosure, indicating social VR's potential in delivering mental health services such as individual and group counseling and therapy. This study provides evidence that social VR can enhance social interaction and communication while serving as a platform for professional mental health care, a venue that has yet to be explored in previous studies.
College Students’ Perceived Credibility of Health Information on YouTube

This work‐in‐progress study explores users' perceived credibility of health‐related YouTube videos and proposes a credibility evaluation framework consisting of twelve criteria across four levels: source, content, creator, and interaction. College students who use YouTube for health information were invited to participate in an online survey. A pilot study was carried out with a small sample size. The findings from the pilot study showed that participants frequently accessed health videos, mainly for specific diseases, treatments, mental health, nutrition, and fitness. There were statistically significant associations between source and interaction, as well as source and creator. Further analyses with a larger sample size will be performed and reported at the 2023 ASIS&T annual meeting. We believe the findings from this study could enhance the understanding of users' attitudes and behaviors of seeking and sharing health information on YouTube.
Investigating Academic Graph‐Based Factors behind Funding Success in National Institutes of Health

While major funding agencies are striving for diversity and fairness, the mechanisms behind funding success have yet to be fully elucidated. Existing studies reveal valuable evidences about the effect of the applicant's individual attributes, e.g., gender and age, on the funding success. However, the relationship between funding success and academic activities, e.g., collaborator's characteristics, remains underexplored. This work collects massive scholarly data from open academic graphs and public data about National Institutes of Health awards to investigate the effect of various academic graph‐based factors on the “K to R” success. Leveraging a heterogeneous graph model for predicting the “K to R” success, we regard the gain in the model performance of a factor as a proxy variable for the magnitude of its effect on the “K to R” success. Our preliminary results suggest that interest by peers in the applicant's research and the timing of the interest are strongly correlated with the outcome. Meanwhile, the applicant's social connections, e.g., their collaborators, can also contribute to the outcome.
Analysis of UK Science Data Ethics Policy: Structure, Content and Governance Network

This study uses the UK as an example to explore the structure, content and governance network of scientific data ethics policies. Adopting grounded theory (GT) and Social Network Analysis (SNA), Nvivo12 is used to analyze and summarize the structure and content of scientific data ethics policy, and Ucinet and Netdraw are used to map governance network reflected in policy. Results indicate that the structure covers governance context, subject and measure. The content of governance context contains context description and data ethics issues analysis. Governance subject consists of defining subjects and facilitating their collaboration. Governance measure includes governance guidance and ethics governance initiatives in the data lifecycle. Governance network indicates that research institution plays a central role in ethics governance and the core of the governance content are ethics governance initiatives and governance guidance.
Spontaneous Learning Environments: Manipulating Readability & Cohesion in Support of Searching as Learning

In this concept paper, we make the case that variables related to reading and comprehension are relevant to the design of searching as learning environments. We propose that measures of cohesion – the lexical and grammatical connectedness within and between texts – be used as signals in retrieval and ranking algorithms for such environments, as cohesion is an important factor in text comprehension and learning. In illustrating this concept, we introduce a use case for learning‐oriented search in which the task is to retrieve a multi‐document set that functions as a spontaneous learning environment. For this task, features of the document set as a whole are important in addition to features of individual documents. In this paper, we focus on the goals of achieving a mid‐range level of readability and cohesion across a set of texts in order to balance comprehensibility with challenge and stimulation.
Investigating the Intersections of Ethics and Artificial Intelligence in the Collections as Data Position Papers

A paradigm shift is currently underway with the emergence of the Collections as Data movement, which advocates the creation and dissemination of cultural heritage collections that are amenable to large‐scale computation to empower both collection managers and users. Although this discourse is beginning to gain some traction in the literature, critical evidence‐based assessments of the opportunities and risks of this process are underexplored. This paper presents the results of a content analysis of the official position statements (n = 83) produced in the Collections as Data forums and written by international professionals working with digital collections. Although preliminary, the analysis presented and discussed here sheds light on the initial reception of the idea of Collections as Data and its articulation in practice. The study represents the first systematic attempt to explore the complexities of the intersection of ethics and artificial intelligence in the context of cultural heritage, aiming at providing a valuable precedent for further elaboration and discussion.
Revisiting the Benefits of Duplicate Questions: Evidence from Knowledge Evolution on Stack Overflow

Stack Overflow (SO) represents one of the most vibrant Question Answering Communities (QACs), providing a crucial platform for developers to pose and respond to questions. SO preserved duplicate questions due to their potential for furnishing additional insights or suggestions. In this paper, we delve into the study of duplicates within SO, with the objective of unraveling their positive value, particularly through the lens of knowledge networks and the evolution. We propose a categorization of knowledge evolution within QACs into two key dimensions: depth and breadth. Our exploration reveals that duplicate questions play a constructive role in fostering both the depth and breadth of knowledge evolution. This finding illuminates the underestimated value of duplicate questions, underlining their significance for the ongoing expansion of knowledge within QACs.
Chinese‐Tibetan Bilingual Knowledge Organization in the Cultural Heritage Domain: A Practice for Traditional Tibetan Festivals

The trend of multilingualism in the web environment has put new demands on the digitization of cultural heritage. However, minority languages in cultural heritage have received little attention in China. This study selects traditional Tibetan festivals, a representative minority cultural heritage in China. Based on constructing a Chinese‐Tibetan bilingual ontology, the cultural and tourism data of Tibet are linked. By further constructing a knowledge graph, a Chinese‐Tibetan Bilingual Tibetan cultural service platform with traditional Tibetan festivals as the core is established.
Imputation and Body Weight Variability Calculation Using Linear and Nonlinear Methods in Data Collected From Digital Smart Scales: Simulation and Validation Study. JMIR mHealth and uHealth, 8 (9)

Background: Body weight variability (BWV) is common in the general population and may act as a risk factor for obesity or diseases. The correct identification of these patterns may have prognostic or predictive value in clinical and research settings. With advancements in technology allowing for the frequent collection of body weight data from electronic smart scales, new opportunities to analyze and identify patterns in body weight data are available. Objective: This study aims to compare multiple methods of data imputation and BWV calculation using linear and nonlinear approaches Methods: In total, 50 participants from an ongoing weight loss maintenance study (the NoHoW study) were selected to develop the procedure. We addressed the following aspects of data analysis: cleaning, imputation, detrending, and calculation of total and local BWV. To test imputation, missing data were simulated at random and using real patterns of missingness. A total of 10 imputation strategies were tested. Next, BWV was calculated using linear and nonlinear approaches, and the effects of missing data and data imputation on these estimates were investigated. Results: Body weight imputation using structural
The Effect of the Fraud Pentagon in Detecting Fraudulent Financial Reporting

T his study aims to examine the factors of fraudulent financial reporting in the banking sector for the 2015-2020 period. Several factors include external pressure, financial targets, change of directors, and frequent number of CEO's picture. Currently, many studies in the field of fraudulent financial reporting have been carried out in the manufacturing industry sector as well as in the mining sector, while the current focus of research is in the banking sector, which has significant differences in characteristics in aspects of leverage, return on assets, and CEO arrogance in financial institutions. This study uses a quantitative approach of to panel data regression using Stata software which connects twelve banks listed on the Indonesian stock exchange with a period of six years from 2015 to 2020. The result of this study indicate that external pressure has a negative effect on fraudulent financial reporting. In addition, financial targets and changes in directors have a positive effect on fraudulent financial reporting. While other result shows that the frequent number of CEO's picture has no effect on fraudulent financial reporting in the banking sector. The limitation of this study is that it has a small sample of banks with a relatively short period of observation time, thus so that the range of observational data is still limited and unable to be generalized to larger companies. In addition, this study uses a quantitative approach, and further studies are expected to extend the cross-sectional and corporate culture wisdom to increase the determination of banking fraudulent financial reporting.
high genetic connectivity for the

Squalus blainville is one of the least studied Mediterranean shark species. Despite being intensively fished in several loca - tions, biological knowledge is limited and no genetic structure information is available. This is the first study to examine the ge - netic structure of S. blainville in the Mediterranean Sea. Considering the high dispersal potential inferred for other squalid sharks, the hypothesis of panmixia was tested based on a 585 bp fragment of the mitochondrial DNA cytochrome c oxidase subunit I gene from 107 individuals and six nuclear microsatellite loci from 577 individuals. Samples were collected across the Ionian, Aegean and Libyan Seas and off the Balearic Islands. Twenty three additional sequences of Mediterranean and South African origin were retrieved from GenBank and included in the mitochondrial DNA analysis. The overall haplotype diversity was high, in contrast to the low nucleotide diversity. Low and non-significant pairwise Φ ST and F ST values along with a Bayesian cluster analysis suggested high connectivity with subsequent genetic homogeneity among the populations studied, and thus a high dispersal potential for S. blainville similar to other squalids. The historical demography of the species was also assessed, revealing a pattern of population expansion since the middle Pleistocene. These findings could be considered in species-specific conservation plans, although sampling over a larger spatial scale and more genetic markers are required to fully elucidate the genetic structure and dispersal potential of S. blainville .
Determining the Predictive Performance of Hybrid Classification Algorithms on Covid-19 Patient Death Rate in Nigeria

— several epidemiological models are being used around the world to project the number of infected individuals and the mortality rates of the COVID-19 outbreak. Advancing accurate prediction models is of utmost importance to take proper actions. Due to the lack of essential data and uncertainty, the epidemiological models have been challenged regarding the delivery of higher accuracy for long-term prediction. The focus of this study is to determine the predictive performance of different classification algorithms on COVID-19 patient death rate in Nigeria. This research aims at determining the predictive accuracy of the various factors contributing to the increase death rate of covid-19 in Nigeria such as patient’s displayed symptoms, patient’s level of education and patient’s age. The primary data used for this study were collected from Akwa Ibom State Covid-19 surveillance and monitoring unit which aided the classification of the components and factors contributing to the spread of the disease. For analysis, the study adopted the following data mining
Flash Droughts in the Wake of Landfalling Atlantic Tropical Cyclones

Using a novel but a proven strategy to detect Flash Droughts (FDs), we identiﬁed four cases out of 30 (˜13%) landfalling Atlantic TCs over the period of 2000-2018 Atlantic hurricane seasons that were associated with FD events in their wake. In all four instances of these FD events, the principal causes were found to be the rapid reduction in precipitation and warming of the surface temperature despite the moderate to weak anomalously wet soil prevalent in the wake of the landfalling TC. These FD cases assume signiﬁcance because they occurred in southeastern US, which is primarily energy limited for evapotranspiration in the summer. Furthermore, all four cases of FD occurred coincidentally with a more widespread, neighboring drought near the landfall region, which suggests that these FD extend these large-scale droughts from the exacerbated conditions in the wake of the landfalling TC
The Richness of English Language During Covid-19 Pandemic: Selected Words and Expressions That Can Be Taught to EFL Students at the Colleges of Health Science and Colleges of Nursing in KSA and Kuwait

The COVID-19 crisis has made the years 2020 and 2021 an unpolitical and spiritual crisis. It has affected virtually everybody in the world and introduced a new normal. Since the beginning of the COVID-19 outbreak, people have been hooked on consuming news media to follow the development of this unprecedented disease. Subsequently, a new language with vocabulary, expressions, and metaphors has appeared in various languages, including English and Arabic. Dictionaries have added new words in English and revised others; they are now fully integrated into our everyday vocabularies. COVID-19 has changed the English language in many ways: it has brought previously obscure medical words to the forefront of everyday speech, made terms related to social isolation more common, and witnessed a shift in meaning in other terms. As linguists, researchers, and teachers gradually return to their classrooms next term (Spring, 2022) we undertook this study to identify 57 English terms, expressions, and metaphors that emerged during the COVID-19 pandemic, either in English-speaking countries or Arabic-speaking countries where English is a first or second language. We deemed the new terminologies necessary for EFL learners in the Gulf Cooperation Countries (GCC) countries. It can serve the purpose of making a list of these words and expressions to be taught to our EFL students at colleges of nursing and health science in Kuwait or Saudi Arabia or any other equivalent colleges in the Arab World. The terms and expressions came from articles, magazines, and English and Arabic dictionaries published during the COVID-19 pandemic.
An on-demand scheduling scheme for mobile charger in wireless rechargeable sensor networks

— Restricted energy of sensor node is a serious concern in wireless sensor networks (WSNs) which causes for loosing data or may be the whole network failure. To overcome this problem the concept of wireless energy transfer (WET) has been introduced which attract huge attention throughout academia and industry to address energy shortages or fulfil the energy requirements. The lifespan of sensor nodes can be extend using WET that restore the battery power of the sensor nodes by recharging the nodes through one or more chargers. However, recharging the nodes in the network is NP-hard problem. In this paper, we present priority scheduling algorithm (PSA) for charging wireless sensor nodes in on-demand wireless rechargeable sensor networks. The lifetime of the sensor nodes is mainly considered as the priority parameters in the proposed PSA algorithm. We simulate the proposed PSA algorithm and compare the results with existing well-known algorithms to show its out performance.
2015 The eﬀect of vertex corrections on the possibility of chiral symmetry breaking, induced by long-range Coulomb repulsion in graphene

In this paper we consider the possibility of chiral (charge or spin density wave) symmetry breaking in graphene due to long-range Coulomb interaction by comparing the results of the Bethe-Salpeter and functional renormalization-group approaches. The former approach performs summation of ladder diagrams in the particle-hole channel, and reproduces the results of the Schwinger-Dyson approach for the critical interaction strength of the quantum phase transition. The renormalization-group approach combines the eﬀect of diﬀerent channels and allows to study the role of vertex corrections. The critical interaction strength, which is necessary to induce the symmetry breaking in the latter approach is found in the static approximation to be α c = e 2 / ( ǫv F ) ≈ 1 . 05 without considering the Fermi velocity renormalization, and α c = 3 . 7 with accounting the renormailzation of the Fermi velocity. The latter value is expected to be however reduced, when the dynamic screening eﬀects are taken into account, yielding the critical interaction, which is comparable to the one in freely suspended graphene. We show that the vertex corrections are crucially important to obtain the mentioned values of critical interactions.