User Information Research Articles

Higher-order network information propagation model based on social impact theory

User relationships are becoming increasingly diverse in current online social networks. This paper utilizes simplicial complexes in higher-order networks to depict multiple user relationships and characterize the topology of social networks. By employing social impact theory and factors such as user interest and information aging to define state transition rules among users, we establish a UAPR information propagation model based on simplicial complexes to simulate the information propagation process in higher-order social networks. The proposed model is simulated on three types of synthetic networks and four real-world simplicial complexes, demonstrating its ability to accurately describe the dynamics and influences of information propagation. Furthermore, our results indicate that different network structures, user interest values, information aging speeds, and intimacy levels significantly influence the information transmission process.

Information needs in bug reports for web applications

Given the widespread popularity and increasing reliance on long-lived web applications (such as Netflix and Facebook), effective and efficient bug reproduction is essential to maintain functionality and user satisfaction throughout the application’s lifetime. Developers use bug reports to localize, reproduce, and eventually fix software bugs. However, the content of bug reports is not always helpful (e.g., due to incomplete or missing information). In this study, we explore what type of information is often missing in bug reports and how that information is presented in them. We manually analyzed the initial and final versions of 1000 bug reports from 10 popular open-source web-based applications. The analysis revealed that, regardless of the type of software (e.g., e-commerce software or personal tools), diagnostic suggestions from developers and end-user usage information are often missing in initial bug reports but only added later throughout the lifetime of a bug report. Also, textual descriptions and screenshots are used most to describe bugs, regardless of the type of bug (e.g., a functional or performance error). The study highlighted the need for improved bug reporting templates and tools to improve bug report quality and efficiency in web application development and maintenance.

Agenda Setting Theory in The Age of Digital Media: An Analytical Perspective

This paper explores agenda-setting theory within digital media. It aims to evaluate changes in these paradigms due to digital platforms and their impact on mass communication theories. The discussion includes a historical overview of agenda-setting theory, grounded in foundational works and expanded by contemporary insights on user agency and information dissemination in the digital age. Using qualitative methods, the study incorporates thematic analysis, content analysis, and interviews with media professionals and users to collect comprehensive data. Key findings indicate that the traditional linear flow of information from media to the public has shifted to a multidirectional exchange influenced by user-generated content and social media dynamics. The study emphasizes the need for scholars to adapt traditional media theories to the participatory nature of modern platforms. This research enhances understanding of current media ecosystems and lays the groundwork for future studies on media influence in complex digital environments.

Reconstructing the soundscape of the ancient Hippodrome of Olympia for an immersive sonic experience of heritage sites based on sound source description in texts

This study attempts to reconstruct and auralize the soundscape of the Hippodrome of Olympia in Greece. This UNESCO world-heritage-listed-site is considered the evidence of the Greek hippodromes. Hippodromes used to have several activities from which different combinations of sound sources created the soundscape. To collect sound sources, description in texts of site is sought by implementing methods of the archaeology of soundscape and the suggested criteria of contextual, internal, and comparative certainty for archaeoacoustics studies. The description of these activities facilitates reconstructing and auralizing the soundscape during different phases of events in the hippodrome. The results of the study showed that the information about the activities on the hippodrome, on similar hippodromes of different civilizations, and on similar hippodromes of later eras are rather sufficient to create a comprehensive soundscape of the site. Auralizing the reconstructed soundscape by using current auralization software and techniques promises of immersive experience of ancient sites that enhances understanding the sonic intangible cultural heritage element and the experience of the ancient soundscape. Furthermore, ancient users' perception of the soundscape can be approached by localizing the sound sources on the site and obtaining the corresponding acoustical properties, providing information of users' response to the sonic outcomes

Recognizing Implicitly Toxic Content Based on Multiple Attention Mechanisms

ABSTRACTToxic content on social media has posed a significant threat to user experience and societal stability. In contrast to explicitly toxic content, implicitly toxic content, lacking overt toxic words, is challenging to identify through single‐text features. Therefore, this study proposes a multi‐feature fusion algorithm to recognize implicit toxic content. Firstly, we collect various features for each post, including text content, likes, comments, user information and other features. Subsequently, employing a multi‐head attention mechanism, we extract and fuse these features. Then, utilizing ensemble learning algorithms, we identify implicitly toxic content based on the fused features. Finally, we analyze the decision‐making process of the model using an interpretable algorithm and derive the most critical features and factors for identifying implicitly toxic content. The experimental results show that the proposed algorithm outperforms algorithms such as BERT, TextCNN, and XGBoost, demonstrating the advantage of multiple features over a single text feature in recognizing implicitly toxic content. In addition, this study provides insights into the decision‐making process of the model and provides more effective toxic content management strategies for social media platforms.

Nintendo 3DS forensics: A secondhand case study

Computer and console-based video games are an important part of the entertainment industry. Such devices may be found in evidence lockers as part of investigations, or overlooked as their intrinsic value to an investigation may not be well-understood. Modern games consoles provide network connectivity and functionality that allows a significant degree of interaction via peer-to-peer connections and/or the Internet. These gaming consoles store settings, user preferences, user information, and can capture photos, audio and video, all of which potentially contain forensic artifacts about a person of interest. Games consoles have a fixed lifespan, eventually superseded by newer models with an expanded range of capabilities. As there are significant numbers of consoles available on the secondhand market, there is clear evidence that older consoles remain in circulation even after production has ceased. What is unclear, however, is the actual extent of forensic data available within these consoles. This paper shares the results of a digital forensic case-study undertaken to assess what artifacts are retrievable based on ‘real-world’ dataset, particularly the aging, but popular Nintendo 3DS series. A total of 47 Nintendo 3DS/2DS handheld systems were purchased secondhand. They were forensically imaged then examined to identify what artifacts are commonly found ‘in the wild’ on these often overlooked systems. Results presented in this paper provide guidance to digital forensic investigators of what may be realistically obtained from these non-traditional devices.

Keamanan siber sebagai fondasi pengembangan aplikasi keuangan mobile: Studi literatur mengenai cybercrime dan mitigasinya

This study examines the importance of cybersecurity in mobile financial applications, particularly in the face of rising cybercrime threats. The aim of this research is to provide deeper insights into the significance of cybersecurity in mobile financial apps and to develop approaches that financial companies can adopt to protect their users' data and information. The research employs a qualitative descriptive method using a systematic literature review (SLR) approach. Meta-synthesis analysis is applied to synthesize data from 26 journal articles published between 2019 and 2024. The findings reveal that cybercrime in the financial and FinTech industries is driven by internal factors such as weak security systems, lack of system updates, limited human resource competencies, and careless user behavior. External factors include malware attacks, unclear regulations, and the use of advanced technology. To counter these, it is necessary to implement technologies such as firewalls and blockchain, strong risk management, enhanced network infrastructure, the establishment of cybersecurity teams, the development of clear regulations, and user education to raise awareness and improve cybersecurity. Therefore, the implementation of a comprehensive cybersecurity strategy is crucial in maintaining the integrity and trust of users in mobile financial applications.

A Systematic Review of Privacy Policy Literature

An organization’s privacy policy states how it collects, stores, processes, and shares its users’ personal information. The growing number of data protection laws and regulations as well as the numerous sectors where the organizations are collecting user information, has led to the investigation of privacy policies with regards to their accessibility, readability, completeness, comparison with organization’s actual data practices, use of machine learning/natural language processing for automated analysis, and comprehension/perception/concerns of end-users via summarization/visualization tools and user studies. However, there is limited work on systematically reviewing the existing research on this topic. We address this gap by conducting a systematic review of the existing privacy policy literature. To this end, we compiled and analyzed 202 papers (published till 31 st December 2023) that investigated privacy policies. Our work advances the field of privacy policies by summarizing the analysis techniques that have been used to study them, the data protection laws/regulations explored, and the sectors to which these policies pertain. We provide actionable insights for organizations to achieve better end-user privacy.

Empowering Library Services through User‐Centric Analysis of Co‐loan Patterns

ABSTRACTBy examining loan data from public libraries in South Korea, we seek to understand patterns in user borrowing behaviors and explore thematic connections among borrowed books. The subject headings of 55.5 million book sets borrowed by individual users on the same day were analyzed using ITEM2VEC. We have identified 40 subject heading communities through cosine similarity of each subject vector, and we have labeled each community using a large language model. Two prominent communities were identified: Global Modern Literature and Novels and Children's Literature, Fairy Tales, and Folklore. The latter community was associated with a diverse array of subjects, indicating an expansion in children's reading preferences. The study results will be useful for improving collection development and the relevance of book recommendations, as well as for incorporating user information behavior into traditional library material classification schemes.

Web-Based DICOM Viewers: A Survey and a Performance Classification.

The standard for managing image data in healthcare is the DICOM (Digital Imaging and Communications in Medicine) protocol. DICOM web-viewers provide flexible and accessible platforms for their users to view and analyze DICOM images remotely. This article presents a comprehensive evaluation of various web-based DICOM viewers, emphasizing their performance in different rendering scenarios, browsers, and operating systems. The study includes a total of 16 web-based viewers, of which 12 were surveyed, and 7 were compared performance-wise based on the availability of an online demo. The criteria for examination include accessibility features, such as available information or requirements for usage, interface features, such as loading capabilities or cloud storage, two-dimensional (2D) viewing features, such as the ability to perform measurements or alter the viewing window, and three-dimensional (3D) viewing features, such as volume rendering or secondary reconstruction. Only 4 of the viewers allow for the viewing of local DICOM files in 3D (other than MPR(Multiplanar reconstruction)). Premium software offers a large amount of features with overall good performance. One of the free alternatives demonstrated the best efficiency in both 2D and 3D rendering but faces challenges with missing 3D rendering features in its interface, which is still in development. Other free options exhibited slower performance, especially in 2D rendering but have more ready-to-use features on their web app. The evaluation also underscores the importance of browser choice, with some browsers performing much better than the competition, and highlights the significance of hardware when dealing with rendering tasks.

Authorship Dynamics in Multidisciplinary Research: A Focus on Library and Information Science Professionals in RRIJM

This study looks into bibliometric studies in library and information science (LIS) to learn more about the influence of professional collaborations and multidisciplinary publication. It centers on user behaviour, digital libraries, and information management. The study uses bibliometric methodologies to examine authorship trends, geographic distribution, research paper length, and references. The results enhanced comprehension of the importance of library science in academic communities by emphasizing its function in handling intricate problems and promoting information sharing. Data from the Research Review International Journal of Multidisciplinary has been used in the study.

Design of an Intelligent medication box system

In the context of today's intelligent development, in order to help improve the living experience of the elderly, convenient and intelligent "smart medicine boxes" have begun to enter their lives. The intelligent medication box system designed in this article aims to assist elderly people in taking medication, while monitoring and providing feedback on daily medication usage information. Using microcontroller technology and Bluetooth wireless communication technology, when Bluetooth is in contact with a mobile phone, the indicator light of the smart medicine box will light up, the LCD1602 display screen will prompt medication, and the buzzer will sound an alarm, thereby reminding the elderly to take medication at the appropriate time. When the switch of the smart medicine box fluctuates, the mobile app will provide feedback on the switch status of the medicine box, thereby providing specific information on the medication taking of the elderly. The future application prospects of this system are extremely broad.

Your Eyes on Speed: Using Pupil Dilation to Adaptively Select Speed-Reading Parameters in Virtual Reality

Rapid Serial Visual Presentation (RSVP) improves the reading speed for optimizing the user's information processing capabilities on Virtual Reality (VR) devices. Yet, the user's RSVP reading performance changes over time while the reading speed remains static. In this paper, we evaluate pupil dilation as a physiological metric to assess the mental workload of readers in real-time. We assess mental workload under different background lighting and RSVP presentation speeds to estimate the optimal color that discriminates the pupil diameter varying RSVP presentation speeds. We discovered that a gray background provides the best contrast for reading at various presentation speeds. Then, we conducted a second study to evaluate the classification accuracy of mental workload for different presentation speeds. We find that pupil dilation relates to mental workload when reading with RSVP. We discuss how pupil dilation can be used to adapt the RSVP speed in future VR applications to optimize information intake.

The Impact of Data Privacy on Users' Smartphone App Adoption Decisions

Rich user information is gained through user tracking and power mobile smartphone applications. Apps thereby become aware of the user and their context, enabling intelligent and adaptive applications. However, such data poses severe privacy risks. Although users are only partially aware of them, awareness increases with the proliferation of privacy-enhancing technologies. How privacy literacy and raising privacy concerns affect app adoption is unclear; however, we hypothesize that it leads to a lower adoption rate of data-heavy smartphone apps, as non-usage often is the user's only option to protect themselves. We conducted a survey (N=100) to investigate the relationship between privacy-relevant app- and publisher characteristics with the users' intention to install and use it. We found that users are especially critical of contentful data types and apps with rights to perform actions on their behalf. On the other hand, the expectation of a productive benefit induced by the app can increase the app-adoption intention. Our findings show which aspects designers of privacy-enhancing technologies should focus on to meet the demand for more user-centered privacy.

Examining the Effect of Knowledge Seeking on Knowledge Contribution in Q&A Communities.

Based on motivational theory, this study investigated the effect of users' knowledge seeking on users' knowledge contribution in question-and-answer (Q&A) communities. We collected 4643 samples from the largest social Q&A platform in China (Zhihu) and applied a mediation effect test to the data. The results showed that knowledge seeking affects intrinsic motivations (altruism and self-efficacy) and extrinsic motivations (social support, group identity, and reputation), further affecting knowledge contribution. Our findings indicated that Q&A communities should be concerned with users' intrinsic and extrinsic motivations to ensure balanced knowledge exchange on social Q&A platforms, ultimately fostering long-term stability and growth. Existing research has mainly focused on a single behavioral state, such as knowledge seeking or knowledge contribution, and has paid little attention to the connection between these two types of user information behaviors. This study aimed to fill this gap by revealing the mechanisms through which users' knowledge seeking affects their knowledge contribution.

Особенности утечек информации ограниченного доступа в Российской Федерации

According to official data, over the past year the number of personal data leaks has increased 4 times. The number of published personal data in 2023 exceeds the total population of the Russian Federation by 50 million. The study systematizes the statistics of information leaks in the context of impact factors and the composition of leaked user information in 2022-2023. In the course of analyzing statistical data from the largest vendors in Russia, the main characteristic features of personal data leaks in 2023 were identified and the vulnerabilities of domestic cyberspace were identified. The author identified the imperfections of legislative regulation of the processes of ensuring comprehensive protection of personal data and proposed directions for leveling the identified vulnerabilities.

Analysis of the Saluni Santri Dictionary from Dr. Ali Al-Qasimy’s Perspective

The existence of the components of dictionary preparation that have been proposed by experts in the field can be used as a benchmark in assessing the ideal dictionary. This research aims to analyze the existence of the components in the Santri Saluni Dictionary by using Dr. Ali Al-Qasimy's perspective. The method used in this research is library research with descriptive characteristics. The results of the study found that the Santri Saluni Dictionary meets 16 of the 25 components proposed by Dr. Ali Al-Qasimy. These components are: a.) the initial part: the purpose of preparing the dictionary, the sources used, the background of the preparation, instructions for using the dictionary, grammar guidelines, the amount of material in the dictionary, the meaning of symbols, and also other information in the form of print and publisher info, and table of contents, b.) the main part: the font used, the column model, phonetic information, morphological information, semantic information, and examples of word usage, c.) the final part: table components, bibliography and brief information about the dictionary on the back cover.

A two-stage recommendation optimization algorithm based on item popularity and user features

Financial product recommendation algorithms are mainly product-centered. This article proposes a two-stage recommendation optimization algorithm based on item popularity and user features, named CPCF-TSP, that can make full use of the demographic characteristics of users and mitigate the problem of users being more inclined to choose “hot” financial products. A popularity weight factor is introduced to normalize popularity and modify Pearson's similarity function. The modified Pearson's similarity function is combined with popularity normalization and user features to improve modeling performance. The two-stage recommendation optimization procedure was combined with a collaborative filtering algorithm to improve recommendation precision. CPCF-TSP fully considers user features in building a hybrid recommendation model and solves the problem of user cold-start. It can also mitigate popularity deviations and improve recommendation precision. MovieLens data and Santander Bank client trading data were used in a case study. The results show that the algorithm reduces inaccuracy in the calculation of the weights for recommendation popularity and similarity and is especially suitable for recommending financial products in which user information can be easily collected and the number of users is far greater than the number of products considered.

Design of a JSP based Mobile Phone Repair Reservation System

With the development of the times, mobile phones are becoming more and more popular. The increase in the number of mobile phones will lead to an increase in the number of mobile phone repairs. Developing a mobile phone repair appointment system can be beneficial for mobile phone repairs. The mobile phone repair reservation system adopts the B/S mode, using Eclipse software as the system development tool and Java programming language for system development. The system database adopts SQL Server database. In system development, JSP and Servlet technologies are used to help users repair their phones more conveniently, while also benefiting maintenance personnel. The mobile phone repair reservation system designed in this paper consists of a front-end user module and a back-end administrator module. The front-end module implements functions such as registering and logging in for front-end maintenance personnel, modifying personal information, publishing, viewing, modifying, and deleting appointments for maintenance personnel, registering and logging in for front-end users, modifying personal information, making appointments, viewing appointments, and canceling appointments. The backend module enables administrators to modify personal information, view and delete personal information of users and maintenance personnel, view and delete appointment information, and other functions.

Factors influencing user's health information discernment abilities in online health communities: based on SEM and fsQCA.

Online health communities have become the main source for people to obtain health information. However, the existence of poor-quality health information, misinformation, and rumors in online health communities increases the challenges in governing information quality. It not only affects users' health decisions but also undermines social stability. It is of great significance to explore the factors that affect users' ability to discern information in online health communities. This study integrated the Stimulus-Organism-Response Theory, Information Ecology Theory and the Mindsponge Theory to constructed a model of factors influencing users' health information discernment abilities in online health communities. A questionnaire was designed based on the variables in the model, and data was collected. Utilizing Structural Equation Modeling (SEM) in conjunction with fuzzy-set Qualitative Comparative Analysis (fsQCA), the study analyzed the complex causal relationships among stimulus factors, user perception, and the health information discernment abilities. The results revealed that the dimensions of information, information environment, information technology, and information people all positively influenced health information discernment abilities. Four distinct configurations were identified as triggers for users' health information discernment abilities. The core conditions included information source, informational support, technological security, technological facilitation, and perceived risk. It was also observed that information quality and emotional support can act as substitutes for one another, as can informational support and emotional support. This study provides a new perspective to study the influencing factors of health information discernment abilities of online health community users. It can provide experiences and references for online health community information services, information resource construction and the development of users' health information discernment abilities.