The effects of visual formats on Facebook health-related posts: evidence from eye movement analysis

PurposeThis study aimed to provide user-centered evidence for health professionals to make optimal use of images for the effective dissemination of health information on Facebook (FB).Design/methodology/approachUsing an eye-tracking experiment and a survey method, this study examined 42 participants' reading patterns as well as recall and recognition outcomes with 36 FB health information posts having various FB post features.FindingsThe findings demonstrated that FB posts with text-embedded images received more attention and resulted in the highest recall and recognition. Meanwhile, compared to text-embedded images, visual only images yielded less effective recall of information, but they caught the viewers' attention; graphics tended to attract more attention than photos. For effective communication, the text features in FB posts should align with the formats of the images.Practical implicationsThe findings of this study provide practical implications for health information disseminators by suggesting that text-embedded images should be used for effective health communication.Originality/valueThis study provided evidence of users' different viewing patterns for FB health information posts and the relationship between FB post types and recall and recognition outcomes.

Mapping the quantity, quality and structural indicators of Asian (48 countries and 3 territories) research productivity on cloud computing

PurposeThe purpose of this study was to map the quantity (frequency), quality (impact) and structural indicators (correlations) of research produced on cloud computing in 48 countries and 3 territories in the Asia continent.Design/methodology/approachTo achieve the objectives of the study and scientifically map the indicators, data were extracted from the Scopus database. The extracted bibliographic data was first cleaned properly using Endnote and then analyzed using Biblioshiny and VosViewer application software. In the software, calculations include citations count; h, g and m indexes; Bradford's and Lotka's laws; and other scientific mappings.FindingsResults of the study indicate that China remained the most productive, impactful and collaborative country in Asia. All the top 20 impactful authors were also from China. The other most researched areas associated with cloud computing were revealed to be mobile cloud computing and data security in clouds. The most prominent journal currently publishing research studies on cloud computing was “Advances in Intelligent Systems and Computing.”Originality/valueThe study is the first of its kind which identified the quantity (frequencies), quality (impact) and structural indicators (correlations) of Asian (48 countries and 3 territories) research productivity on cloud computing. The results are of great importance for researchers and countries interested in further exploring, publishing and increasing cross country collaborations related to the phenomenon of cloud computing.

A worldwide quantitative review of the iSchools' archival education

PurposeArchival studies have long been a critical part of information education around the world. This paper attempts to provide a worldwide overview of archival education among main information schools worldwide and find out their similarity and differences to suggest measures for the development of archival education.Design/methodology/approachQuantitative research is conducted including ten elements of the iSchools' archival education which are (1) geographical distribution, (2) names of degrees, (3) names of concentration/specialization, (4) names of academic units offering the programs, (5) levels of academic units offering the programs, (6) study mode, (7) credit requirement for program completion, (8) percentage of required credits, (9) capstone requirements and (10) other accreditations. Programs among different regions are compared.FindingsThe study found that 43 out of 96 iSchool members from 13 countries/regions offer a total of 45 master's level archival education, and most of them are from North America. Both similarities and differences among the schools are identified and discussed.Practical implicationsThis study’s findings suggest that iSchools may explore the possibility of organizing more conferences and forums to exchange ideas on archival studies and education issues. The iSchool community could contribute to this traditional field by attracting more members worldwide and cooperating with other accreditation organizations of archival education.Originality/valueMost research on archival education focuses on just regional or country-based issues, and scant research explores a global view.

Assessing individual behavior towards adoption of telemedicine application during COVID-19 pandemic: evidence from emerging market

PurposeThis study attempts to gain insight into what factors influence individual behavior towards the adoption of telemedicine application during coronavirus disease 2019 (COVID-19) pandemic. The research model incorporates two well-known theories namely the extended unified theory of acceptance and use of technology (UTAUT2) and DeLone and McLean information success model to examine individual behavior towards the adoption of telemedicine application.Design/methodology/approachThe research design of this study is based on quantitative research approach. During research survey, 350 valid responses were received from Pakistani citizens and examined to understand citizen's behavior towards the adoption of telemedicine applications. The research model was empirically tested with the latest statistical approach namely variance-based structural equation modeling (VB-SEM).FindingsThe results of the structural equation modeling have revealed that altogether performance expectancy, social influence, effort expectancy, facilitating condition, habit, hedonic motivation, price values, information quality, system quality and service quality explained 77.9% variance in determining user behavior towards adoption of telemedicine application. The predictive relevance of the research model was found substantial in measuring user behavior to adopt telemedicine applications. The research framework is further extended with moderating role of perceived severity between the relationship of user intention and actual usage behavior. Results confirmed that the positive relationship between intention to adopt telemedicine health application and usage behavior will be stronger when perceived severity is higher.Practical implicationsTheoretically, this study integrates extended UTAUT2 and DeLone and McLean information success model and contributes to e-health literature. Practically, this research suggests that by improving user performance expectancy and effort expectancy, managers and healthcare professionals can boost user confidence towards the adoption of telemedicine applications.Originality/valueThis study is unique as it integrates the extended UTAUT2 with DeLone and McLean information success model and perceived severity to investigate user behavior towards adoption of telemedicine application during COVID-19 pandemic. Additionally, the integration of theories contributes to information system literature in the context of the adoption of telemedicine applications.

User experience research on social robot application

PurposeSocial robot, a subtype of robots that is designed for the various interactive services for human, which must deliver superior user experience (UX) by expressing human-like social behavior or service and emotional sensitivity. This study develops a social robot app called the “Music Buddy” in ASUS Zenbo that provides a situational music based on the users' electroencephalogram (EEG) data. The research uses this app to explore its UX criteria and the prioritization of human robot interaction (HRI).Design/methodology/approachThe research methodologies include the both system development and decision analysis for the social robot. The first part is to design and develop a social robot app. The second part is to investigate the criteria of HRI through the Analytic Hierarchy Process (AHP) from UX aspects.FindingsIn view of the results of the AHP, the first-layer criteria consist of personalized function, easy-to-use the system and intelligent process. In terms of prioritization of multi-criteria, the overall ranking discloses the nine criteria in order including autonomy for robot, easy-to-use EEG device, accurate music preference, simple operations for brainwave device and easy-to-use applications, active music recommendation, automatic updates of music and easy-to-use robot as well as fast detection for emotion.Originality/valueThis research includes a self-developed social robot app and its UX research using AHP. This paper contributes to the improvement and innovation of the social robot design according to the results of UX research on HRI of social robot.

Research on public emotional polarization and public opinion evolution of OTC and learning during the COVID-19 epidemic: taking the topic of OTC on Zhihu as an example

PurposeThe outbreak and continuation of COVID-19 have spawned the transformation of traditional teaching models to a certain extent. The Chinese Ministry of Education’s guidance on “keep learning and teaching during class suspension” has made OTC and learning (OTC) become routinized, and the public’s emotional attitudes toward OTC have also evolved over time. The purpose of this study is to segment the emotional text data and introduce it into the topic model to reveal the evolution process and stage characteristics of public emotional polarity and public opinion of OTC topics during public health emergencies in the context of social media participation. The research has important guiding significance for the development of OTC and can influence and improve the efficiency and effect of OTC to a certain extent. The analysis of online public opinion can provide suggestions for the government and media to guide the trend of public opinion and optimize the OTC model.Design/methodology/approachThis paper takes the topic of “OTC” on Zhihu during the COVID-19 epidemic as an example, combined with the characteristics of public opinion changes, chooses Boson emotional dictionary and time series analysis method to build an OTC network public opinion theme evolution analysis framework that integrates emotional analysis and topic mining. Finally, an empirical analysis of the dynamic evolution of the communication network for each stage of the life cycle of a specific topic is realized.FindingsThis paper draws the following conclusions: (1) Through the emotional value table and the change trend chart of the number of comments, the analysis found that the number of positive comments is greater than the number of negative comments, which can be inferred that the public gradually accepts “OTC” and presents a positive emotional state. (2) By observing the changing trend of the average daily emotional value of the public, it is found that the overall emotional value shows a stable development trend after a large fluctuation. From the actual emotional value and the fitted emotional value curve, it can be seen that the overall curve fit is good, so ARIMA (12, 1, 6) can accurately predict the dynamic trend of the daily average emotional value in this paper. Therefore, based on the above-mentioned public opinion, emotional analysis research, relevant countermeasures and suggestions are put forward, which is conducive to guiding the development direction of public opinion in a positive way.Originality/valueTaking the topic of “OTC” in Zhihu as an example, this paper combines Boson emotional dictionary and time series to conduct a series of research analyses. Boson emotional dictionary can analyze the public’s emotional tendency, and time series can well analyze the intrinsic structure and complex features of the data to predict the future values. The combination of the two research methods allows for an adequate and unique study of public emotional polarization and the evolution of public opinion.

What drives continuance intention to use a food-ordering chatbot? An examination of trust and satisfaction

PurposeArtificial intelligence (AI) customer service chatbots are a new application service, and little is known about this type of service. This study applies service quality, trust and satisfaction to predict users' continuance intention to use a food-ordering chatbot.Design/methodology/approachThe proposed model and hypotheses are tested using online questionnaire responses to collect users' perceptions of such services. One hundred and eleven responses of actual users were received.FindingsEmpirical results show that anthropomorphism and service quality, such as problem-solving, are the antecedents of trust and satisfaction, while satisfaction has the most significant direct effect on the users' intention.Originality/valueThe results provide further useful insights for service providers and chatbot developers to improve services.

Study on the law of aging in Library and Information Science

PurposeAging research has traditionally been an important research topic in the field of Library and Information Science(LIS). The study of aging enables us to grasp the extent of development and the status of aging in LIS. The purpose of this paper is to explore the current law of aging in LIS and to research the impact of interdisciplinary citations on the aging of the discipline.Design/methodology/approachBy using citation analysis methods and fitting them using the Barnett aging model, the aging law of LIS is explored with the help of aging indicators such as citing half-life and Price Index. For interdisciplinary study, the authors explore the pattern of interdisciplinary citations distribution by distinguishing LIS and non-LIS citations by journal name.FindingsThe results show that LIS is currently aging slowly and has reached a relatively mature stage. It has a high reliance on archival literature. The interdisciplinary citations distribution is broadly consistent with the overall citation distribution, and interdisciplinary citations can increase the age of applicability of the literature.Originality/valueBased on LIS journal citation data, the paper validates the rationality of Barnett model applied in the field of literature aging research using nonlinear regression analysis, which can effectively reflect the aging law of literature and enable scholars to predict its development trend more accurately. In addition, according to the current trend of interdisciplinary citation, this paper explores the impact of interdisciplinary citations on the aging of the literature and provides a new idea for future aging research.

Information Literacy Skills among Library and Information Science Professionals: a forecaster of Research Support Services

PurposeThe present research aims to gauge the Information Literacy Skills (ILSs) of the University Library and Information Science Professionals (LISPs) of Pakistan and consider it as a forecaster of improved Research Support Services (RSSs).Design/methodology/approachThe purposive sampling method through a questionnaire was applied and administered (online and offline) to assemble data from LISPs of 219 universities of Pakistan. The questionnaire covered the eight factors of ILSs and four of RSSs.FindingsThe regression model illustrates that the predicted variation of ILSs in RSSs is statistically significant. The coefficient of determination (R2) indicates that ILSs predict 70% variance in RSSs. Furthermore, the beta coefficient demonstrates that the input value of “managing findings” toward improved RSSs is moderately high as compared to other factors of ILSs. Therefore, the study concludes that ILSs of LISPs are a prerequisite for their professional growth to improve their RSSs.Originality/valueThe research has discovered the whole levels of ILSs and RSSs of the university LISPs of Pakistan. The study recommends raising the ILSs of LISPs to provide more efficient RSSs.

Characterizing response quantity on academic social Q&A sites: a multidiscipline comparison of linguistic characteristics of questions

PurposeAs academic social Q&A networking websites become more popular, scholars are increasingly using them to meet their information needs by asking academic questions. However, compared with other types of social media, scholars are less active on these sites, resulting in a lower response quantity for some questions. This paper explores the factors that help explain how to ask questions that generate more responses and examines the impact of different disciplines on response quantity.Design/methodology/approachThe study examines 1,968 questions in five disciplines on the academic social Q&A platform ResearchGate Q&A and explores how the linguistic characteristics of these questions affect the number of responses. It uses a range of methods to statistically analyze the relationship between these linguistic characteristics and the number of responses, and conducts comparisons between disciplines.FindingsThe findings indicate that some linguistic characteristics, such as sadness, positive emotion and second-person pronouns, have a positive effect on response quantity; conversely, a high level of function words and first-person pronouns has a negative effect. However, the impacts of these linguistic characteristics vary across disciplines.Originality/valueThis study provides support for academic social Q&A platforms to assist scholars in asking richer questions that are likely to generate more answers across disciplines, thereby promoting improved academic communication among scholars.