Aslib Journal of Information Management

Publisher:: Emerald Group Publishing Limited
Publication date:: 2021-02-01

ISBN:: 2050-3806

Issue Number

Latest documents

Detecting the research structure and topic trends of social media using static and dynamic probabilistic topic models
Purpose: A huge volume of published research articles is available on social media which evolves because of the rapid scientific advances and this paper aims to investigate the research structure of social media. Design/methodology/approach: This study employs an integrated topic modeling and text mining-based approach on 30381 Scopus index titles, abstracts, and keywords published between 2006 and 2021. It combines analytical analysis of top-cited reviews with topic modeling as means of semantic validation. The output sequences of the dynamic model are further analyzed using the statistical techniques that facilitate the extraction of topic clusters, communities, and potential inter-topic research directions. Findings: This paper brings into vision the research structure of social media in terms of topics, temporal topic evolutions, topic trends, emerging, fading, and consistent topics of this domain. It also traces various shifts in topic themes. The hot research topics are the application of the machine or deep learning towards social media in general, alcohol consumption in different regions and its impact, Social engagement and media platforms. Moreover, the consistent topics in both models include food management in disaster, health study of diverse age groups, and emerging topics include drug violence, analysis of social media news for misinformation, and problems of Internet addiction. Originality/value: This study extends the existing topic modeling-based studies that analyze the social media literature from a specific disciplinary viewpoint. It focuses on semantic validations of topic-modeling output and correlations among the topics and also provides a two-stage cluster analysis of the topics.
Guest editorial: Human–computer interactions: investigating the dark side and proposing a model based on an empirical collection of studies
Reviewing topics of COVID-19 news articles: case study of CNN and China daily
Purpose: The purpose of this study is to analyze the topics of COVID-19 news articles for better obtaining the relationship among and the evolution of news topics, helping to manage the infodemic from a quantified perspective. Design/methodology/approach: To analyze COVID-19 news articles explicitly, this paper proposes a prism architecture. Based on epidemic-related news on China Daily and CNN, this paper identifies the topics of the two news agencies, elucidates the relationship between and amongst these topics, tracks topic changes as the epidemic progresses and presents the results visually and compellingly. Findings: The analysis results show that CNN has a more concentrated distribution of topics than China Daily, with the former focusing on government-related information, and the latter on medical. Besides, the pandemic has had a big impact on CNN and China Daily's reporting preference. The evolution analysis of news topics indicates that the dynamic changes of topics have a strong relationship with the pandemic process. Originality/value: This paper offers novel perspectives to review the topics of COVID-19 news articles and provide new understandings of news articles during the initial outbreak. The analysis results expand the scope of infodemic-related studies.
How innovation types affect users' continuous knowledge sharing intention: a self-determination perspective
Purpose: This research aims to investigate the effects of innovation types (exploratory innovation vs. exploitative innovation) on users' psychological perceptions (perceived self-improvement and prosocial impact) and continuous knowledge sharing intention and the moderating effects of monetary incentives. Design/methodology/approach: The research model was developed based on the self-determination theory. A two-study approach involving an online survey (n = 338) and an online experiment (n = 160) was employed to collect quantitative data. Structural equation modeling and variance analysis were adapted to analyze the data. Findings: The results show that exploratory innovation leads to higher perceived self-improvement among users than exploitative innovation, whereas exploitative innovation leads to higher perceived prosocial impact than exploratory innovation. The perceived self-improvement and perceived prosocial impact positively affects users' continuous knowledge sharing intention. Monetary incentives moderate the relationships among perceived self-improvement, perceived prosocial impact and continuous knowledge sharing intention. Originality/value: This research highlights the role of users' experience of initial participation in forming continuous knowledge sharing intentions and also reveals the effectiveness of monetary incentives in different types of innovation activities. The findings provide a more comprehensive understanding of the antecedents of users' continuous knowledge sharing behavior, offering new insights and recommendations for managerial practitioners.
What motivates people to continuously engage in online task-oriented check-ins? The role of perceived social presence
Purpose: Online task-oriented check-ins (i.e. OTOCs) are popular means of tracking personal progress in certain fields. This study focused on the use of OTOC platforms and explored the predictors of individuals' continuing usage intention. Design/methodology/approach: A model was proposed to understand Chinese users' continuous intention of OTOCs based on the UTAUT framework. Perceived social presence was also incorporated as a predictor of continuance intention of OTOC platforms. A survey of 397 users of the OTOC platforms was conducted in Nanjing, China. Findings: Performance expectancy, hedonic motivation, and habit had direct, positive influence on the continuous use intention, whereas effort expectancy and social influence were not significant predictors of continuance intention of OTOCs. Perceived social presence was a significant, indirect predictor of intention to continuously use the OTOCs, and the relationship was mediated by performance expectancy, hedonic motivation, and habit. Originality/value: This study distinguished OTOCs from other modes of self-tracking and extended the UTAUT framework by incorporating perceived social presence as a predictor of continuous technology use in the context of OTOCs. This study also provided a deeper understanding of the interrelations between the explanatory variables of the model that have been identified as robust in previous literature on technology use.
Internal-led cyber frauds in Indian banks: an effective machine learning–based defense system to fraud detection, prioritization and prevention
Purpose: The study aims to overview the different types of internal-led cyber fraud that have gained mainstream attention in recent major-value fraud events involving prominent Indian banks. The authors attempted to identify and classify cyber frauds and its drivers and correlate them for optimal mitigation planning. Design/methodology/approach: The methodology opted for the identification and classification is through a detailed literature review and focus group discussion with risk and vigilance officers and cyber cell experts. The authors assessed the future of cyber fraud in the Indian banking business through the machine learning–based k-nearest neighbor (K-NN) approach and prioritized and predicted the future of cyber fraud. The predicted future revealing dominance of a few specific cyber frauds will help to get an appropriate fraud prevention model, using an associated parties centric (victim and offender) root-cause approach. The study uses correlation analysis and maps frauds with their respective drivers to determine the resource specific effective mitigation plan. Findings: Finally, the paper concludes with a conceptual framework for preventing internal-led cyber fraud within the scope of the study. A cyber fraud mitigation ecosystem will be helpful for policymakers and fraud investigation officers to create a more robust environment for banks through timely and quick detection of cyber frauds and prevention of them. Research limitations/implications: Additionally, the study supports the Reserve Bank of India and the Government of India's launched cyber security initiates and schemes which ensure protection for the banking ecosystem i.e. RBI direct scheme, integrated ombudsman scheme, cyber swachhta kendra (botnet cleaning and malware analysis centre), National Cyber Coordination Centre (NCCC) and Security Monitoring Centre (SMC). Practical implications: Structured and effective internal-led plans for cyber fraud mitigation proposed in this study will conserve banks, employees, regulatory authorities, customers and economic resources, save bank authorities’ and policymakers’ time and money, and conserve resources. Additionally, this will enhance the reputation of the Indian banking industry and extend its lifespan. Originality/value: The innovative insider-led cyber fraud mitigation approach quickly identifies cyber fraud, prioritizes it, identifies its prominent root causes, map frauds with respective root causes and then suggests strategies to ensure a cost-effective and time-saving bank ecosystem.
What influences user participation in an online health community? The stimulus-organism-response model perspective
Purpose: The purpose of this paper is to understand the effect of platform characteristics (i.e. media richness and interactivity) on individual perception (i.e. outcome expectations) and consequent behavioral response (i.e. user participation in online health communities (OHCs)) based on the stimulus-organism-response (S-O-R) model. Design/methodology/approach: This study developed a research model to test the proposed hypotheses, and the proposed model was tested using partial least squares structural equation modeling (PLS-SEM) for which data were collected from 321 users with OHC experience using an online survey. Findings: The empirical results show the following: (1) the three dimensions of media richness significantly affect the three outcome expectations, except that richness of expression has no significant effect on the outcome expectation of health self-management competence. (2) Human-to-human interaction significantly affects the three outcome expectations. Moreover, compared with human-to-human interaction, human-to-system interaction has a stronger impact on the outcome expectation of health self-management competence. (3) The three outcome expectations have a significant influence on user participation in OHCs. Originality/value: This study extends the understanding about how platform characteristics (i.e. media richness and interactivity) motivate user participation in the context of OHCs. Drawing on the S-O-R model, this study reveals the underlying mechanisms by which media richness and interactivity are associated with outcome expectations and by which outcome expectations is associated with user participation in OHCs. This study enriches the literature on media richness, interactivity, outcome expectations and user participation in OHCs, providing insights for developers and administrators of OHCs.
What do experts say about the conditions affecting customer knowledge management in academic libraries? An integrated perspective
Purpose: The purpose of the present study was to design an axial coding pattern for customer knowledge management (CKM) to identify the conditions affecting it from the perspective of experts in public university libraries. Design/methodology/approach: The current study used a qualitative approach. To collect and analyze data, the grounded theory method with a three-stage strategy of open, axial and selective coding was employed. The research instrument was a semi-structured in-depth interview and the data were categorized using MAXQDA 10 software. The sample of the study consisted of 26 experts from Iranian public universities who were selected through a combined targeted non-random sampling procedure (targeted and snowball). The necessary data were obtained through specialized interviews with 9 faculty members and 17 managers of public university libraries. Findings: In the present study, 106 open coding, 35 axial concepts, and 16 selective general categories were identified as the conditions affecting CKM development in academic libraries in the form of causal conditions, intervening conditions, strategies conditions, context conditions, and consequences conditions around the core layer of CKM development. The identification of these conditions led to the development of a paradigmatic pattern for the research. Originality/value: There is no record of research on developing empirical studies in libraries using an analysis of the conditions affecting CKM development in the form of an axial coding pattern. The present research contributed to closing this research gap. The axial coding pattern proposed in this study can serve as a guide for implementing CKM in academic libraries as well as increasing customer loyalty.
The role of personality traits in participation in an Online Cancer Community
Purpose: The purpose of this study was to investigate how personality traits influence participative behaviour in an Online Cancer Community (OCC). Design/methodology/approach: Qualitative semi-structured interviews were conducted with 42 users of one of the largest OCCs in Australia – Cancer Council Online Community in New South Wales (NSW). Findings: The results showed that extraversion, emotional stability and agreeableness traits influence posting behaviour, whereas the conscientiousness trait influences lurking behaviour. The openness trait did not affect either posters or lurkers’ online behaviour. Research limitations/implications: The research highlights the pivotal role of personality traits in users’ decisions to post or lurk using a multi-theory perspective that combined the social exchange theory and the Five-Factor Model. Future studies should explore personality traits that can benefit from online participation in an OCC to transition only lurkers who may benefit from posting. Practical implications: Insights from the study inform OCC practitioners and moderators when designing the OCC platform. Except for the openness trait, lurkers and posters exhibited different attitudes, which indicates that integrating these findings in the OCC design can facilitate adopting strategies to elicit more participation by OCC users. Originality/value: This is the first study that explored the role of personality traits in users’ decisions to participate in an OCC.
Research on the propagation and governance of public opinion information under the joint action of internal and external factors
Purpose: Under the new media environment, while enjoying the convenience brought by the propagation of public opinion information (referred to as public opinion), learning the evolution process of public opinion and strengthening the governance of the spreading of public opinion are of great significance to promoting economic development and maintaining social stability as well as effectively resisting the negative impact of its propagation. Design/methodology/approach: Thinking about the results of empirical research and bibliometric analysis, this paper focused on introducing key factors such as information content, social strengthening effects, etc., from both internal and external levels, dynamically designed public opinion spreading rules and netizens' state transition probability. Subsequently, simulation experiments were conducted to discuss the spreading law of public opinion in two types of online social networks and to identify the key factors which influencing its evolution process. Based on the experimental results, the governance strategies for the propagation of negative public opinion were proposed finally. Findings: The results show that compared with other factors, the propagation of public opinion depends more on the attributes of the information content itself. For the propagation of negative public opinion, on the one hand, the regulators should adopt flexible guidance strategy to establish a public opinion supervision mechanism and autonomous system with universal participation. On the other hand, they still need to adopt rigid governance strategy, focusing on the governance timing and netizens with higher network status to forestall the wide-diffusion of public opinion. Practical implications: The research conclusions put forward the enlightenment for the governance of public opinion in management practice, and also provided decision-making reference for the regulators to reasonably respond to the propagation of public opinion. Originality/value: Our research proposed a research framework for the discussion of public opinion propagation process and had important practical guiding significance for the governance of public opinion propagation.