Paper analyzes the ways in which an educational digital game can promote digital inclusion through its structures and mechanics.

Presentation paper for the 2017 International Conference on Knowledge Management. This paper examines the level of awareness and understanding of the various issues, challenges, and training needs associated with research data management for Hacettepe University researchers

This workshop is presented by members of a University of North Texas research team. First, the team will overview their experience as members of the research team and share experience in areas such as trust formation, team roles, productivity, work-life balance, faculty-students interaction, peer and faculty mentorship, dissertation preparation, and job seeking. Second, the workshop will discuss and brainstorm how this format can be implemented for organizations both with faculty-student teams and with peer-directed teams. Finally, successes and challenges are openly discussed with audience.

Paper conducts a literature review on articles focused on organizational resilience in the context of innovation.

Paper reviews research in Design Thinking applications in didactic experiences with children.

Paper attempts to define the phases of the development process within the Front End of Innovation (FEI) through a systematic literature review.

Arising in China in December 2019, the novel coronavirus (COVID-19) soon spread to other countries worldwide including Bangladesh. Mass media and social media platforms played an important role in providing Coronavirus related information and news as they enable people to share news as well as personal experiences with one another rapidly. Since little is known about COVID-19, various fake news spread across social media that panicked people into making panic decisions. The primary objective of this study is to examine how social media is spreading fake or unauthentic news during the time of COVID-19 pandemic. This study also focuses on how the university students of Bangladesh are playing their roles in the spread of fake news in social media. An online survey was conducted to reach a wide number of university students who own at least one social media account. A well-structured questionnaire was designed containing both open and close ended questions. Google forms was used to build the survey instrument. The questionnaire was distributed to the students using different social media platforms. Collected data were analyzed using SPSS version 20 and MS Excel. The study showed that the students sometimes received COVID-19 related fake news. The main reason behind …

This poster compares and contrasts four different provenance models.

Poster for the 2018 International Conference on Knowledge Management. This poster compares and contrasts four different provenance models.

This paper describes the development of the SciThink App, a mobile knowledge management tool to help scientists and researchers query, download, and read scientific and technological literature.

This paper discusses the scientific memory of the public library in the Brazilian National Institute of Technology (INT/Brazil) from the perspective of control devices and information policy regime.

Presentation paper for the 2017 International Conference on Knowledge Management. This paper uses the Brenda Dervin sense making model to explain human behavior and way of reasoning with making purchasing decisions of smart thermostats.

With an increasing flood of data and at the same time changing requirements, making the relevant information available in the right context to a customer and within the company for the respective development-, technical- and service-departments is a key success factor for many companies and at the same time an enormous challenge. The problem with folders and filing data in tree structures is that information about an object is scattered across different aspects. Access to this information is only possible if the respective aspects are known. In a semantic network, each object exists only once, all information about this object comes together at this point and it can still be accessed within different contexts. Such a network can be changed at any time and further aspects can be added as needed: semantic machine learning, in order to be able to react flexibly to new requirements. Semantic networks combine functions of ontologies, topic maps, taxonomies and thesauri. They model complex relationships and directly transform large amounts of structured and unstructured content into networked units of knowledge. In this way, computer-readable and computer-usable knowledge bases are created. The creation and maintenance of semantic networks is demand-driven and interactive between humans and computers. …

With an increasing flood of data and at the same time changing requirements, making the relevant information available in the right context to a customer and within the company for the respective development-, technical- and service-departments is a key success factor for many companies and at the same time an enormous challenge. The problem with folders and filing data in tree structures is that information about an object is scattered across different aspects. Access to this information is only possible if the respective aspects are known. In a semantic network, each object exists only once, all information about this object comes together at this point and it can still be accessed within different contexts. Such a network can be changed at any time and further aspects can be added as needed: semantic machine learning, in order to be able to react flexibly to new requirements. Semantic networks combine functions of ontologies, topic maps, taxonomies and thesauri. They model complex relationships and directly transform large amounts of structured and unstructured content into networked units of knowledge. In this way, computer-readable and computer-usable knowledge bases are created. The creation and maintenance of semantic networks is demand-driven and interactive between humans and computers. …

The 17th International Conference on Knowledge Management was held in the historic city of Potsdam, Germany. Since the conference was among the first post-pandemic face to face conferences, the overall theme of the 17th edition of the ICKM conference rightly focused on “Knowledge, Uncertainty and Risks: From individual to global scale” at different levels of analysis and agency. This document highlighted one of the panels that provide an overview of the different methodologies and theories of sense-making from several of the seminal originators of sensemaking.

Paper presents a system for viewing interactive sources aimed at producing accessible digital material.

Global warming is the term used to describe critical environmental issues and concerns. Social media such as Twitter provides a platform for people to share information, exchange ideas, and express their opinions about current and timely issues. This study utilized contextual analysis to analyze data collected from Twitter for the hashtag "global warming" during the period 2010 & 2011. Using sentiment analysis and topic modeling, the study aimed first at assessing people's perception towards global warming issues, and second study the impact of misinformation from the standpoint of social noise on people's perception of global warming during critical environmental events. The outcome of this study helps create a better understanding of the environmental issues discussed on social media. The sentiment analysis from the data analyzed so far shows that most of the tweets were based on Twitter users' personal opinions and not science. The topic modeling results suggest that Twitter users typically tweeted when a major environmental event occurred due to global warming. Topic modeling also aids in the identification of terms that is associated with social noise. The presence of social noise suggests that misinformation does exist and spreads faster.

Despite continued improvements to HIV/AIDS treatment and awareness, HIV transmission rates remain high among men who have sex with men (MSM). Online consumer health information targeting high risk MSM through social media and geosocial networking (GSN) apps have shown to be successful HIV intervention strategies. This review article addresses (1) the efficacy and acceptance of delivering consumer health information about pre-exposure prophylaxis (PrEP) and HIV prevention through GSN apps, (2) the impact of online and social media communities in the discussion and delivery of information about PrEP and HIV interventions, and (3) on-going and possible future research and the role of information professionals.

Paper discusses the concept of brand consolidation and it's application in emerging social movements in the case of the #MeToo movement.

Soft skills have become increasingly important in the workplace, particularly in knowledge management (KM). Developing a knowledge culture in an organization depends on the soft skills of leaders. KM literature, however, does not often discuss the development and teaching of soft skills that can facilitate the success of knowledge management in organizations. This presentation will present the challenge of teaching and learning soft skills as well as a proposed framework to address those challenges.

Poster for the 2018 International Conference on Knowledge Management. This poster uses a questionnaire to identify which information sources respondents would use in specific situations and which qualities of those sources were most important to them.

This paper anonymously applies seven spatial syntax methods to seven grocery stores for the purpose of identifying and characterizing work space genotypes.

This paper will report on a research to develop Speaker Independent, Continuous Speech Recognizer for Kafi Noonoo (Afro-Asiatic language that belongs to North Omotic sub family in Ethiopia) using Hidden Markov Modeling technique. The portable and open source toolkit called Hidden Markov Model (HMM) Toolkit is used to perform the experiment. The development of HMM based Automatic Speech Recognition (ASR) requires both text and speech corpus for training and testing the HMM. In order to have a model that incorporates different features of the language, we included the different dialects of Kafi Noonoo in the corpus and then prepared the training and test corpus from the scratch, and after preprocessing we have sampled and performed feature extraction using Mel Frequency Cepstral Coefficients (MFCC) feature extraction technique.

Building predictive models for companies often relies on inference using historical data of companies in the same industry sector. However, companies are similar across a variety of dimensions that should be leveraged in relevant prediction problems. This is particularly true for large, complex organizations which may not be well defined by a single industry and have no clear peers. To enable prediction using company information across a variety of dimensions, we create an embedding of company stocks, Stock2Vec, which can be easily added to any prediction model that applies to companies with associated stock prices. We describe the process of creating this rich vector representation from stock price fluctuations and characterize what the dimensions represent. We then conduct comprehensive experiments to evaluate this embedding in applied machine learning problems in various business contexts. Our experiment results demonstrate that the four features in the Stock2Vec embedding can readily augment existing cross-company models and enhance cross-company predictions.