Search

In this article, we are reporting the findings of a usability study of opinion mining systems' visualizations. The objectives of this study are to first to rank the visualizations of the opinion mining systems and second to identify important visualization metrics. A questionnaire survey was designed to ask users their level of agreement or disagreement about the 11 selected visualizations against a set of information visualization metrics on a Likert scale. The data were collected by conducting seminars and using a web-based online questionnaire (N = 146). The collected data were analyzed using descriptive statistics and an independent sample t-test to rank the visualizations and investigate differences between perceptions of the two groups of respondents (the participants of the seminars and the online questionnaire), respectively. The results revealed that simple, eye pleasing, easy to understand, user-friendly visualizations with less pre-knowledge required rated higher than others. It is concluded that the participants of the online questionnaire mostly required more pre-knowledge to comprehend the visualizations as compared to the participants of the seminars. The important information visualization metrics are eye pleasing, easy to understand, user-friendly, informative design, usefulness, and representation style. The results of this study could aid in the design and development of visualizations for opinion mining systems. [ABSTRACT FROM AUTHOR]

This study was conducted to investigate the moderating effect of health professional's working experience on the relationship between factors of Health Information System Security Policies Compliance Behaviour (HISSPC) model. A survey (i.e., n = 454) was conducted to test the differences between high experience and low experience health professionals who were Health Information System (HIS) users. The HISSPC model was tested using partial least squares (PLS) approach with results indicating the coefficient of determination (i.e., R2) for high experience group (i.e., 63 percent)to be slightly higher than the low experience group (i.e., 60 percent). Statistical differences were noted for the relationship between management support and user's compliance behaviour in both groups,with stronger relationship forlow experience HIS users compared to high experience HIS users. In contrast, perceived susceptibility was found to significantly influence highly experienced users to comply with HIS security policies, however it had no significant effect for the low experience group.The overall moderating effect size for high experience users was approximately 0.07 (i.e. small) and no moderating effect was observed for the low experience group (i.e., ƒ2 = 0.01). It was believed that the findings will provide better guidelines to fellow researchers and policy makers in improving information security behaviour among health professionals in hospitals, particularly those with varying working experiences. [ABSTRACT FROM AUTHOR]

This study investigated the factors that might affect the use of social media in e-learning, particularly targeting the use of Facebook, Twitter and YouTube. Questionnaire design was based on Push-Pull-Mooring framework, and distributed to students and academicians in local universities (N = 455). Five significant predictors were found, viz. E-learning Perception, Convenience, Academic Reasons, Ease of Use and Social Networking. A further analysis revealed younger respondents were more enthusiastic in using social media in e-learning, particularly for Academic Reasons, Social Networking and Ease of Use. The findings indicate that students and academicians are open to the idea of using social media in e-learning, more apparent among the younger ones. It is believed that integration of social media in e-learning will enhance communication and collaboration among students and academicians. [ABSTRACT FROM AUTHOR]

This paper presents an enhanced vector space model, Multi-Term Adjacency Keyword-Order Model, to improve the relevancy of search results, specifically document search. Our model is based on the concept of keyword grouping. The keyword-order relationship in the adjacency terms is taken into consideration in measuring a term's weight. Assigning more weights to adjacency terms in a query order results in the document vector being moved closer to the query vector, and hence increases the relevancy between the two vectors and thus eventually results in documents with better relevancy being retrieved. The performance of our model is measured based on precision metrics against the performance of a classic vector space model and the performance of a Multi-Term Vector Space Model. Results show that our model performs better in retrieving more relevant results based on a particular search query compared to both the other models. [ABSTRACT FROM AUTHOR]

Conversational systems are gaining popularity rapidly. Consequently, the believability of the conversational systems or chatterbots is becoming increasingly important. Recent research has proven that learning chatterbots tend to be rated as being more believable by users. Based on Raj's Model for Chatterbot Trust, we present a model for allowing chatterbots to determine the degree of contradictions in contradictory statements when learning thereby allowing them to potentially learn more accurately via a form of discourse. Some information that is learnt by a chatterbot may be contradicted by other information presented subsequently. Choosing correctly which information to use is critical in chatterbot believability. Our model uses sentence structures and patterns to compute contradiction degrees that can be used to overcome the limitations of Raj's Trust Model, which takes any contradictory information as being equally contradictory as opposed to some contradictions being greater than others and therefore having a greater impact on the actions that the chatterbot should take. This paper also presents the relevant proofs and tests of the contradiction degree model as well as a potential implementation method to integrate our model with Raj's Trust Model. [ABSTRACT FROM AUTHOR]

This article reports findings from a study in which a total of 110 youths were interviewed to analyze the overall pattern of Short Message Service (SMS) usage among Malaysians. Structured interview questionnaires were used to collect the required data. The selected respondents were between 17 and 25 years old, an age category that has proven to represent the most active SMS users worldwide. Descriptive statistics including frequencies and mean values were used to analyze the data. The results indicate that Malaysian youths are as active SMS users as youths in other countries, with the majority sending between five to seven messages daily. As for gender differences, females are found to be more actively involved in SMS activities compared to the males. The findings should prove interesting for those examining the use of SMS among the younger users, especially in an Asian country such as Malaysia. [ABSTRACT FROM AUTHOR]

Hand anthropometry and gender influences on Short Message Service (SMS) usage satisfaction were investigated using structured questionnaire interviews with 110 participants. The collected data were then filtered, resulting in a total of 73 participants. Hand-size, thumb length, circumference and mobile phone dimensions were recorded. Focus was on keypad design factors, which include: key size, shape, layout, texture, simplicity and space between keys. Females were found to be more satisfied with the key size and layout than males. Significant differences were noted among subjects with different hand-size with respect to key size and space between keys. One of the recommended improvements is to have larger keys with more space between them for those with large hand-size. The results obtained can be used by mobile phone designers to design customized mobile phones; for example, mobile phones that suit users with larger hands and thumbs, especially males. [ABSTRACT FROM AUTHOR]

Background: Organisational interoperability (OIoP) of the Healthcare Information System (HIS) is crucial for the success of HIS, however little is known about the impact of institutional factors. Objective: This cross-sectional study aimed to investigate the direct effect of institutional factors on OIoP for HIS in public sector hospitals in Malaysia. Methods: A conceptual OIoP framework was developed using the Personal Health Systems Interoperability and Refined eHealth European Interoperability frameworks. A self-administered questionnaire survey was used to solicit data from 300 healthcare professionals. Data were assessed through an Exploratory Factor Analysis followed by a Confirmatory Factor Analysis. Results: Structured equation modelling revealed Security and Privacy Compliance, and Stakeholder Engagement and Awareness to significantly and positively affect OIoP (R 2 = 0.380). Conclusion: Healthcare organisations should prioritise clear and effective policies and regulations and enough budget and resources for the suggested framework., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Background: The HIV epidemic continues to grow fastest among men who have sex with men (MSM) in Malaysia in the presence of stigma and discrimination. Engaging MSM on the internet using chatbots supported through artificial intelligence (AI) can potentially help HIV prevention efforts. We previously identified the benefits, limitations, and preferred features of HIV prevention AI chatbots and developed an AI chatbot prototype that is now tested for feasibility and acceptability., Objective: This study aims to test the feasibility and acceptability of an AI chatbot in promoting the uptake of HIV testing and pre-exposure prophylaxis (PrEP) in MSM., Methods: We conducted beta testing with 14 MSM from February to April 2022 using Zoom (Zoom Video Communications, Inc). Beta testing involved 3 steps: a 45-minute human-chatbot interaction using the think-aloud method, a 35-minute semistructured interview, and a 10-minute web-based survey. The first 2 steps were recorded, transcribed verbatim, and analyzed using the Unified Theory of Acceptance and Use of Technology. Emerging themes from the qualitative data were mapped on the 4 domains of the Unified Theory of Acceptance and Use of Technology: performance expectancy, effort expectancy, facilitating conditions, and social influence., Results: Most participants (13/14, 93%) perceived the chatbot to be useful because it provided comprehensive information on HIV testing and PrEP (performance expectancy). All participants indicated that the chatbot was easy to use because of its simple, straightforward design and quick, friendly responses (effort expectancy). Moreover, 93% (13/14) of the participants rated the overall chatbot quality as high, and all participants perceived the chatbot as a helpful tool and would refer it to others. Approximately 79% (11/14) of the participants agreed they would continue using the chatbot. They suggested adding a local language (ie, Bahasa Malaysia) to customize the chatbot to the Malaysian context (facilitating condition) and suggested that the chatbot should also incorporate more information on mental health, HIV risk assessment, and consequences of HIV. In terms of social influence, all participants perceived the chatbot as helpful in avoiding stigma-inducing interactions and thus could increase the frequency of HIV testing and PrEP uptake among MSM., Conclusions: The current AI chatbot is feasible and acceptable to promote the uptake of HIV testing and PrEP. To ensure the successful implementation and dissemination of AI chatbots in Malaysia, they should be customized to communicate in Bahasa Malaysia and upgraded to provide other HIV-related information to improve usability, such as mental health support, risk assessment for sexually transmitted infections, AIDS treatment, and the consequences of contracting HIV., (©Min Hui Cheah, Yan Nee Gan, Frederick L Altice, Jeffrey A Wickersham, Roman Shrestha, Nur Afiqah Mohd Salleh, Kee Seong Ng, Iskandar Azwa, Vimala Balakrishnan, Adeeba Kamarulzaman, Zhao Ni. Originally published in JMIR Human Factors (https://humanfactors.jmir.org), 26.01.2024.)

Background: Health information systems are innovative products designed to improve the delivery of effective healthcare, but they are also vulnerable to breaches of information security, including unauthorised access, use, disclosure, disruption, modification or destruction, and duplication of passwords. Greater openness and multi-connectedness between heterogeneous stakeholders within health networks increase the security risk., Objective: The focus of this research was on the indirect effects of management support (MS) on user compliance behaviour (UCB) towards information security policies (ISPs) among health professionals in selected Malaysian public hospitals. The aim was to identify significant factors and provide a clearer understanding of the nature of compliance behaviour in the health sector environment., Method: Using a survey design and stratified random sampling method, self-administered questionnaires were distributed to 454 healthcare professionals in three hospitals. Drawing on theories of planned behaviour, perceived behavioural control (self-efficacy (SE) and MS components) and the trust factor, an information system security policies compliance model was developed to test three related constructs (MS, SE and perceived trust (PT)) and their relationship to UCB towards ISPs., Results: Results showed a 52.8% variation in UCB through significant factors. Partial least squares structural equation modelling demonstrated that all factors were significant and that MS had an indirect effect on UCB through both PT and SE among respondents to this study., Conclusion: The research model based on the theory of planned behaviour in combination with other human and organisational factors has made a useful contribution towards explaining compliance behaviour in relation to organisational ISPs, with trust being the most significant factor. In adopting a multidimensional approach to management-user interactions via multidisciplinary concepts and theories to evaluate the association between the integrated management-user values and the nature of compliance towards ISPs among selected health professionals, this study has made a unique contribution to the literature.

The increasing use and ubiquity of the Internet facilitate dissemination of word-of-mouth through blogs, online forums, newsgroups, and consumer's reviews. Online consumer's reviews present tremendous opportunities and challenges for consumers and marketers. One of the challenges is to develop interactive marketing practices for making connections with target consumers that capitalize consumer-to-consumer communications for generating product adoption. Opinion mining is employed in marketing to help consumers and enterprises in the analysis of online consumers' reviews by highlighting the strengths and weaknesses of the products. This paper describes an opinion mining system based on novel review and feature ranking methods to empower consumers and enterprises for identifying critical product features from enormous consumers' reviews. Consumers and business analysts are the main target group for the proposed system who want to explore consumers' feedback for determining purchase decisions and enterprise strategies. We evaluate the proposed system on real dataset. Results show that integration of review and feature-ranking methods improves the decision making processes significantly.