Discovering hashtag trails with cross-platform hashtag search engines: a state-of-art analysis

Although the hashtag convention was originally initiated by Twitter, it has become a common functionality across multiple social media platforms. As hashtags have become universal and linked across multiple social media platforms, the issue involves how users can search hashtags beyond the boundary of individual social media platform. This study aims to investigate the industry trends in hashtag search engines using a morphological analysis and particularly focuses on those engines supporting hashtag searching across platforms instead of on single platform (i.e., Twitter). As a preliminary result, this study found that the innovation of hashtags has added value to the social media universe and transcended borders of social media. Additionally, this study found that new hashtag functionalities have been developed to address user information needs; hashtags can be interconnected through the emerging hashtag search engines; and the hashtag trails may be profiled to gain more insights into the stories behind the hashtags

Selfies of Twitter Data Stream through the Lens of Information Theory: A Comparative Case Study of Tweet-trails with Healthcare Hashtags

Little research in information system has been carried out on the subject of user’s choice of different components when composing a tweet through the analytical lens of information theory. This study employs a comparative case study approach to examine the use of hashtags of medical-terminology versus lay-language in tweet-trails and (1) introduces a novel H(x) index to reveal the complexity in the statistical structure and the variety in the composition of a tweet-trail, (2) applies radar graph and scatter plot as intuitive data visualization aids, and (3) proposes a methodological framework for structural analysis of Twitter data stream as a supplemental tool for profile analysis of Twitter users and content analysis of tweets. This systematic framework is capable of unveiling patterns in the structure of tweet-trails and providing quick and preliminary snap shots (selfies) of Twitter data stream because it’s an automatic and objective approach which requires no human intervention

Toward an Understanding of Data Literacy

As the interest in data grows, much attention has been paid to data literacy, and multiple perspectives and understandings to define data literacy have emerged from varying conceptual contexts. However, there remains a lack of agreement regarding the scope of data literacy across disciplines. This study attempts to define data literacy holistically through a meta-synthesis approach. The study found three distinct themes for data literacy: as skills required for data-driven decision making, as activities for research data services, and a set of practices for data lifecycle

Navigating the role of mobile technologies in shaping information behavior: A meta-synthesis

Mobile technology, primarily via smartphones, has become increasingly ubiquitous in the modern world, and this change is impacting information behavior in important ways. As LIS educators, we must study this new phenomenon and incorporate it in our teaching in order to stay current in the information science field. With this goal in mind, we used the relatively new meta-synthesis methodology to collect qualitative studies that examined the intersection of mobile technology and information behavior, systematically evaluating them for patterns and trends that provide insight into technology-driven change in behavior we are witnessing. Through this process we identified four primary ways mobile technology is affecting information behavior, and these will be incorporated into a graduate level Information Behavior cours

Getting Smarter: Definition, Scope, and Implications of Smart Libraries

This paper describes a meta-synthesis of existing qualitative research on smart libraries to demonstrate the transition of technology changing to meet users' needs

What we need: Project managers` evaluation of top management actions required for software development projects

Web 2.0 is now an important internet application because of the integration of social interaction and web technologies. Previous information system studies usually specified their research context as a utilitarian system or hedonic system and the results were concluded within one specific system type. Web 2.0 application provides a flexible environment for different kinds of user motivations that can be used for utilitarian or hedonic purpose. This study extended the Technology Acceptance Model (TAM) by introducing a moderating factor into the model, in order to study users’ behavioral intentions in a Web 2.0 environment. We designed two task types of user motivation and conducted our experiment on two Web 2.0 websites. According to the PLS (Partial Least Squares) analysis, this study demonstrated that utilitarian and hedonic purposes had a moderating effect on the relationship between perceived belief and user attitude as well as the relationship between perceived information quality and perceived belief in the Web 2.0 application. The relationship between perceived usefulness and attitude was stronger in the utilitarian user motivation; whereas the relationship between perceived ease of use and attitude was stronger when the user had hedonic motivation to use the Web 2.0 application. We also found that perceived information quality had significant impact on the perceived usefulness and perceived ease of use

Exploring An Individual’s Intention to Use Blogs: The Roles of Social, Motivational and Individual Factors

Blogs are a new type of media for social interaction; they have become very popular, and have shown their influence throughout our society. However, little is known about what motivates an individual to participate in blogging activities. This study aims to explore how an individual\u27s intention is influenced by social, motivational and individual factors. A survey, involving 283 subjects, was conducted to examine the proposed model. The results revealed that personal innovativeness in the domain of information technology (PIIT), perceived usefulness and perceived enjoyment have direct impacts on a persons\u27 intent to use blogs. On the other hand, factors such as subjective norms and blog self-efficacy influence an individual\u27s motivational factors; these factors, in turn, influence an individual\u27s behavioral intention in regard to blog usage. The findings of this study not only contribute to a theoretical building of those factors that effect blog usage, but also provide implications to practitioners for understanding and promoting blog usage

Unfolding Research Data Services: An Information Architecture Perspective

This paper describes the use of a content analysis with the lens of information architecture to better understand how research data services are organize in North American academic library websites, and to what extent the research data lifecycle is supported within these services

Unfolding Research Data Services: An Information Architecture Perspective

Poster presented at the 2018 ACM/IEEE Joint Conference on Digital Libraries. This poster describes the use of a content analysis with the lens of information architecture to better understand how research data services are organize in North American academic library websites, and to what extent the research data lifecycle is supported within these services

Ontology-based Fuzzy Markup Language Agent for Student and Robot Co-Learning

An intelligent robot agent based on domain ontology, machine learning mechanism, and Fuzzy Markup Language (FML) for students and robot co-learning is presented in this paper. The machine-human co-learning model is established to help various students learn the mathematical concepts based on their learning ability and performance. Meanwhile, the robot acts as a teacher's assistant to co-learn with children in the class. The FML-based knowledge base and rule base are embedded in the robot so that the teachers can get feedback from the robot on whether students make progress or not. Next, we inferred students' learning performance based on learning content's difficulty and students' ability, concentration level, as well as teamwork sprit in the class. Experimental results show that learning with the robot is helpful for disadvantaged and below-basic children. Moreover, the accuracy of the intelligent FML-based agent for student learning is increased after machine learning mechanism.Comment: This paper is submitted to IEEE WCCI 2018 Conference for revie