This research aims to understand how Business process management (BPM) can be applied for the improvement of Information Technology service management (ITSM) processes. A case study is conducted for the improvement of the time performance of the incident management process, since it is pointed as a quick win for ITSM. The results obtained identified three best practices—activity automation, activity

Digital disinformation presents a challenging problem for democracies worldwide, especially in times of crisis like the COVID-19 pandemic. In countries like Singapore, legislative efforts to quell fake news constitute relatively new and understudied contexts for understanding local information operations. This paper presents a social cybersecurity analysis of the 2020 Singaporean elections, which took

Analyze and understand how to combine data warehouse with business intelligence tools, and other useful information or tools to visualize KPIs are critical factors in achieving the goal of raising competencies and business results of an organization The main objective of this paper is to present the development of a BI platform, using DW tools to create graphs and detailed reports for the Constructel

The 2020 coronavirus pandemic has heightened the need to flag coronavirus-related misinformation, and fact-checking groups have taken to verifying misinformation on the Internet. We explore stories reported by fact-checking groups PolitiFact, Poynter and Snopes from January to June 2020. We characterise these stories into six clusters, then analyse temporal trends of story validity and the level of

When a group of people works to achieve a common goal, they refer to collaborative work, which is based on the philosophy of interaction and collaboration, that is about working in conjunction with other individuals to achieve that goal and seeking to reach effective results. For this, it is necessary to start from effective communication, which will lay on the foundations to achieve true collaboration

Supported by an environment that is increasingly immersed in digital transformation, universities are facing important organizational changes in both tangible and intangible structures. Digital transformation isn’t all about technology, there is a human side of the story. Leadership is seen as a key issue in any process of change. However, leaders of professional and knowledge-based institutions, like

A small number of individuals infected within a community can lead to the rapid spread of the disease throughout that community, leading to an epidemic outbreak. This is even more true for highly contagious diseases such as COVID-19, known to be caused by the new coronavirus SARS-CoV-2. Mathematical models of epidemics allow estimating several impacts on the population and, therefore, are of great

This paper presents a new social media phenomenon that sees users lying about their deceptive motivations by either dishonestly claiming that they are not bots or by asserting that real news is actually fake news. We analyzed the use of the #FakeNews and #NotABot hashtags in Twitter data collected on the 2019 Canadian federal elections. Our findings show that the #FakeNews hashtag was most likely to

A holy grail for military, diplomatic, and intelligence analysis is a valid set of software agent models that act as the desired ethno-political factions so that one can test the effects of alternative courses of action in different countries. This article explains StateSim, a country modeling approach that synthesizes best-of-breed theories from across the social sciences and that has helped numerous

Innovation failure knowledge sharing plays an important role in reducing the probability of repeated failure of subsequent innovation and improving innovation ability of virtual research organization. However, it is very difficult for members to actively share the innovation failure knowledge without incentives. To promote the sharing behavior of innovation failure knowledge in virtual research organization

The purpose of this research is to analyse the characteristics and behaviour of an organization over the course of 100 months of the courtship, infancy, and go-go stages of its lifecycle. Moreover, the causal feedback loops and stock-and-flow diagrams of each stage of the organizational lifecycle are plotted. The PAEI framework proposed by Adizes and the system dynamics approach are employed to understand

With the rise of online platforms where individuals could gather and spread information came the rise of online cybercrimes aimed at taking advantage of not just single individuals but collectives. In response, researchers and practitioners began trying to understand this digital playground and the way in which individuals who were socially and digitally embedded could be manipulated. What is emerging

Detecting and elucidating botnets is an active area of research. Using explainable, highly scalable Apache Spark-based artificial intelligence, process mining technologies are presented which illuminate bot activity within terrorist Twitter data. A derived hidden Markov model suggests that bot logic uses information camouflage in order to disguise intentions similar to World War II Nazi propagandists

An agent-based model is proposed and tested. This model aims to simulate agency as conceptualized in Bandura's (Am Psychol 37:122–147, 1982; Organ Behav Hum Decis Process 50:248–287; Annu Rev Psychol 52: 1–26) Social cognitive theory. Social cognitive theory has been used to explain the continued underrepresentation of females in certain fields, most notably fields that are associated with engineering

Prior explanations for the observed result that employee cooperation demonstrates both positive and negative relationships with organizational performance often require psychological reactions or cognitions. We use an agent-based model to assume away these effects and demonstrate a possible alternative relying on just three, simple features. These include (1) limits to an employee’s ability to help

Strong demographic faultlines are a potential source of conflict in teams. To study conditions under which faultlines can result in between-group bi-polarization of opinions, a computational model of persuasive argument communication has been proposed. We identify two hitherto overlooked degrees of freedom in how researchers formalized the theory. First, are arguments agents communicate influencing

Diversification involves ongoing decisions about firm boundaries and relatedness. We develop a theoretical model that uses a real-option framework combined with optimal mechanism design to analyze how choices of boundaries and relatedness affect firm performance in the face of tradeoffs between governance and flexibility. We find that: (1) optimal boundaries and relatedness are substitutes in determining

The inhibiting effects of information overload on the behavior of online social media users, can affect the population-level characteristics of information dissemination through online conversations. We introduce a mechanistic, agent-based model of information overload and investigate the effects of information overload threshold and rate of information loss on observed online phenomena. We find that

The knowledge of key network members is generally known to be critical to fuzzy social network analysis. Thus far, most studies aiming to identify critical members have taken network structural centrality measures. Since fuzzy graph cannot effectively depict the multidimensional relationships between the nodes of fuzzy social networks, a fuzzy social network model is developed complying with a mathematical

Even though both collective intelligence and groupthink promote concurrence seeking, studies focused on the relationship between the two are lacking. Therefore, this study aims to explore how to transform groupthink into collective intelligence that contributes to knowledge creation. Three “switching factors”— “knowledge conflict,” “reconsideration,” and “organizational memory”—are defined herein.

Extant research is vertically divided on the question whether exploration and exploitation constitute two ends of a continuum or whether they are orthogonal activities. We suggest that both characterizations are admissible, albeit under different sets of assumptions. Using March’s iconic model, we demonstrate that the continuum conception concerns leveraging an organization’s internal knowledge heterogeneity

We note some future areas for work with cognitive models and agents that as Colbert (I am America (and so can you!), 2007) notes, “so can you”. We present three approaches as something like design patterns, so they can be applied to other architectures and tasks. These areas are: (a) Interacting directly with the screen-as-world. It is now possible for models to interact with uninstrumented interfaces

We present a new mathematical model that predicts the number of users informed and influenced by messages that are propagated in an online social network. Our model is based on a new way of quantifying the tie-strength, which in turn considers the affinity and relevance between nodes. We could verify that the messages to inform and influence, as well as their importance, produce different propagation

Identifying fake news has become an important issue. Increasing usage of social media has led to an increase in the number of people who can be influenced, thus the spread of fake news can potentially impact important events. Fake news has become a major societal issue and a technical challenge for social media companies to identify and has led many to extreme measures, such as WhatsApp deleting two

Ecological models are useful in modeling organizations and their competition over resources. However, the traditional approaches, particularly Blau space models, are restrictive in their dependence on a continuous space. In addition, these models are susceptible to indicating competition in sparsely populated areas of an ecology, resulting in competition being indicated where there are no resources

Online social networks allow users to share a variety of multi-media content on the World Wide Web. The rising popularity of such social networking platforms coupled with limitations in verifying the veracity of shared content has contributed to increase in misinformation on these media. Misinformation content such as fake-news and hoaxes, though often considered innocuous, may have high social cost

We apply a variation of socio-cultural cognitive mapping (SCM) to computer malware features explored previously by Saxe and Berlin that characterized malware binaries as benign or malicious based on 1024 program features derived from a deep neural network-based detection system. In this work, we model the features as attributes within a latent spatial domain using a weighted consensus graph representation

This operations research aims to derive an easy but meaningful method for practitioners to identify key influencers and uncover suppressed narratives within a Twitter topic group. This research employs a new concept called “authentic chatter” (analogous to a grass-roots discourse) in combination with influence metrics, content analysis, and commercial-off-the-shelf social media analysis software (NexaIntelligence)

Social cyber-security is an emergent field defining a multidisciplinary and multimethodological approach to studying and preserving the free and open exchange of information online. This work contributes to burgeoning scholarship in this field by advocating the use of interoperable pipelines of computational tools. We demonstrate the utility of such a pipeline in a case study of Twitter information

This paper describes the design, implementation, and early experiences with a novel agent-based simulator of online media streams, developed under DARPA’s SocialSim Program to extract and predict trends in information dissemination on online media. A hallmark of the simulator is its self-configuring property. Instead of requiring initial set-up, the input to the simulator constitutes data traces collected

The notions of betweenness centrality (BC) and group betweenness centrality (GBC) are widely used in social network analyses. We introduce variants of them; namely, the k-step BC and k-step GBC. The k-step GBC of a group of vertices in a network is a measure of the likelihood that at least one group member will get the information communicated between pairs of vertices through shortest paths within

Although the performance of new product development (PD) is dependent on the structure and formation of design teams, effective configuration of the PD teams remains largely unexplored. According to social network research, teams are often organized in either closely connected or sparse structure. We conceptualize PD projects as collective problem-solving endeavors and develop a computational model

We propose, and test, a model of online media platform users’ decisions to act on, and share, received information. Specifically, we focus on how mental representations of message content drive its spread. Our model is based on fuzzy-trace theory (FTT), a leading theory of decision under risk. Per FTT, online content is mentally represented in two ways: verbatim (objective, but decontextualized, facts)

In this paper, we introduce the concept of social cyber forensics and its usability. Then, we introduce a tool, i.e., Maltego that can be used to study the cross-media affiliation and uncover hidden relations among various online groups. We also provide three stepwise methodologies that leverage Maltego and various open source information to uncover the hidden relationship among (1) Twitter accounts

It is common for organizations to hire workers based on their knowledge, skills, and abilities. However, despite capable workers being hired, productivity may suffer if employees’ motivational needs are not satisfied. We developed an agent-based model to simulate the completion of tasks by teams of workers in an organization. Each worker is described by an ability value and a 3-parameter motive profile

This paper investigates the cause of the collapse of the Second Yatsenyuk Ukrainian government in 2016 and the factions formed throughout the process using a novel method that combines roll call vote analysis and dynamic network analysis. Our findings suggest that a major factor in the dissolution of the coalition government was the 2015 constitutional amendment .We also found that the coalition split

We recently put forth a thesis, the Resolution Thesis, that suggests that cognitive science and generative social science are interdependent and should thus be mutually informative. The thesis invokes a paradigm, the reciprocal constraints paradigm, that was designed to leverage the interdependence between the social and cognitive levels of scale for the purpose of building cognitive and social simulations

The Stock market trend prediction is an efficient medium for investors, public companies and government to invest money by taking into account the profit and risk. The existing studies on the development of stock-based prediction systems rely on data acquired from social media sources (sentiment-based) and secondary data sources (financial-sites). However, the data acquired from such sources is usually

In this study a novel population based meta-heuristic, called controlled showering optimization (CSO) algorithm, for global optimization of unconstrained problems is presented. Modern irrigation systems are equipped with smart tools manufactured and controlled by human intelligence. The proposed CSO algorithm is inspired from the functioning of water distribution tools to model search agents for carrying

Automated social media bots have existed almost as long as the social media environments they inhabit. Their emergence has triggered numerous research efforts to develop increasingly sophisticated means to detect these accounts. These efforts have resulted in a cat and mouse cycle in which detection algorithms evolve trying to keep up with ever evolving bots. As part of this continued evolution, our

Forecasting future productivity is a critical task to every organization. However, the existing methods for productivity forecasting have two problems. First, the logarithmic or log-sigmoid value, rather than the original value, of productivity is dealt with. Second, the objective functions are not consistent with those adopted in practice. To address these problems, a fuzzy polynomial fitting and

Ohio is leading the nation in an epidemic of overdose deaths, most of which are caused by opioids. Through this study we estimate associations between opioid drug overdoses measured as EMS calls and model-predicted drug misuse. The RTI-developed synthetic population statistically represents every household in Cincinnati and allows one to develop a geographically explicit model that links Cincinnati

Much has been made of the importance of the speed at which disinformation diffuses through online social media and this speed is an important aspect to consider when designing interventions. An additional complexity is that there can be different types of false information that travel from and through different communities who respond in various ways within the same social media conversation. Here

The process of diagnosis, intervention, conservation, restoration and maintenance of built cultural heritage requires complete and accurate knowledge about tangible as well as intangible aspects of their past and present. Comprehensive and precise knowledge about built cultural heritage structures, their functionality, location, environment and any sudden disturbance needs to be digitized for long

Since the stakeholder theory was proposed to explain the interaction among its agents, extensive approaches have been developed. However, the literature continues to suggest the development of new methodologies that allow an analysis of the dynamics and uncertainty of the relationships between each agent. In this sense, this research proposes a novel methodology for the treatment of subjective stakeholder

As America’s opioid crisis has become an “epidemic of epidemics,” Ohio has been identified as one of the high burden states regarding fentanyl-related overdose mortality. This study aims to examine changes in the availability of fentanyl, fentanyl analogs, and other non-pharmaceutical opioids on cryptomarkets and assess relationship with the trends in unintentional overdoses in Ohio to provide timely

A significant research topic in the area of computational social choice is the complication of different kinds of dishonest behaviour like manipulation, dominance and bribery. Whereas most of the work on this issue assumes that the opposite party has incomplete knowledge regarding every agent, they did not know the true preferences of other voters. We have analysed the dynamics of voting rules with

Nowadays social media is widely used as the source of information because of its low cost, easy to access nature. However, consuming news from social media is a double-edged sword because of the wide propagation of fake news, i.e., news with intentionally false information. Fake news is a serious problem because it has negative impacts on individuals as well as society large. In the social media the

We describe a computational cognitive model intended to be a generalizable classifier that can provide context-based feedback to semantic perception in robotic applications. Many classifiers (including cognitive models of categorization) perform well at the task of associating features with objects. Underlying their performance is an effective selection of the features used during classification. This

The success of military operations depends on soldiers’ execution of the operation as well as resources used for the operation. However, this does not mean that more men and firepower will ensure victory. Military units, just like any other organization, are collections of distributed elements, and improving the organization or command and control (C2) structure of such elements will ultimately show

Participation in community events such as local festivals can provide people with opportunities to collaborate with community members whom they would have never met otherwise. Furthermore, such collaboration through community events is likely to expand interaction even in daily life. In addition, if the physical properties of a public space in which community events are held change, the number and

Data that continuously track the dynamics of large populations have the potential to revolutionize how we study complex social systems. However, coping with massive, noisy, unstructured, and disparate data streams is not easy. In this paper, we describe a particle filter algorithm that integrates signal processing and simulation modeling to study complex social systems using massive, noisy, unstructured

The emergence of computer-aided diagnostic technology has revolutionized the health sector and by use of medical imaging records, health experts are able to get detailed analysis which enable them in precise diagnosis of gliomas tumors. In this paper, we present an approach that uses domain-specific knowledge together with hybrid image enhancement techniques that provides resulting image(s) with more

The outcome of a work process depends on which tasks are assigned to which employees. However, sometimes optimized assignments based on employees’ qualifications may result in an uneven and ineffective workload distribution. Likewise, an even workload distribution without considering the employee’s qualifications may cause unproductive employee-task matching that results in low performance. This trade-off

As an emerging and promising approach, crowdsourcing-based software development has become popular in many domains due to the participation of talented pool of developers in the contests, and to promote the ability of requesters (or customers) to choose the ‘wining’ solution with respect to their desired quality levels. However, due to lack of a central mechanism for team formation, continuity in the

Finding similar objects based on a query and a distance, remains a fundamental problem for many applications. The general problem of many similarity measures is to focus the search on as few elements as possible to find the answer. The index structures divides the target dataset into subsets. With large amounts of data, the volumes of the subspaces grow exponentially, that will affect the search algorithms

The cursive nature, Nastaliq writing style and a large number of different ligatures make ligature recognition very difficult in Urdu. In this paper, we present a segmentation-free approach to holistically recognize Urdu ligatures. We first generate a rich dataset which contains 17,010 ligatures with different orientation and different degrees of noise. Secondly, the ligatures are clustered (categorized)

The literature on the knowledge management relatively ignores an important concept, the individual knowledge management engagement-the degree to which a knowledge worker is involved with the knowledge management-related activities. This concept is imperative for nurturing the productivity of knowledge workers, knowledge management architecture effectiveness, and innovation. Therefore, this study proposes

A multi-agent system is a useful modeling architecture in business process modeling in the sense that we can naturally implement participants in a real company with software agents. However, analyzing and interpreting the simulation results of multi-agent models tends to be difficult due to the inherent complexity of the models. In this regard, another discipline—process mining—is useful for such purposes