52,196 research outputs found
Understanding âinfluenceâ: An exploratory study of academicsâ process of knowledge construction through iterative and interactive information seeking
The motivation for this study is to better understand the searching and sensemaking processes undertaken to solve exploratory tasks for which people lack pre-existing frames. To investigate peopleâs strategies for that type of task, we focused on âinfluenceâ tasks because, although they appear to be unfamiliar, they arise in much academic discourse, at least tacitly. This qualitative study reports the process undertaken by academics of different levels of seniority to complete exploratory search tasks that involved identifying influential members of their academic community and ârising stars, â and to identify similar roles in an unfamiliar academic community. 11 think-aloud sessions followed by semi-structured interviews were conducted to investigate the role of specific and general domain expertise in the process of information seeking and knowledge construction. Academics defined and completed the task through an iterative and interactive process of seeking and sensemaking, during which they constructed an understanding of their communities and determined qualities of âbeing influentialâ. Elements of the Data/Frame Theory of Sensemaking (Klein et al., 2007) were used as sensitising theoretical constructs. The study shows that both external and internal knowledge resources are essential to define a starting point or frame, make and support decisions, and experience satisfaction. Ill-defined or non-existent initial frames may cause unsubstantial or arbitrary decisions, and feelings of uncertainty and lack of confidence
API : an index for quantifying a scholar's academic potential
In the context of big scholarly data, various metrics and indicators have been widely applied to evaluate the impact of scholars from different perspectives, such as publication counts, citations, -index, and their variants. However, these indicators have limited capacity in characterizing prospective impacts or achievements of scholars. To solve this problem, we propose the Academic Potential Index (API) to quantify scholar's academic potential. Furthermore, an algorithm is devised to calculate the value of API. It should be noted that API is a dynamic index throughout scholar's academic career. By applying API to rank scholars, we can identify scholars who show their academic potentials during the early academic careers. With extensive experiments conducted based on the Microsoft Academic Graph dataset, it can be found that the proposed index evaluates scholars' academic potentials effectively and captures the variation tendency of their academic impacts. Besides, we also apply this index to identify rising stars in academia. Experimental results show that the proposed API can achieve superior performance in identifying potential scholars compared with three baseline methods. © 2019 IEEE
Locating People of Interest in Social Networks
By representing relationships between social entities as a network, researchers can analyze them using a variety of powerful techniques. One key problem in social network analysis literature is identifying certain individuals (key players, most influential nodes) in a network. We consider the same problem in this dissertation, with the constraint that the individuals we are interested in identifying (People of Interest) are not necessarily the most important nodes in terms of the network structure. We propose an algorithm to find POIs, algorithms to collect data to find POIs, a framework to model POI behavior and an algorithm to predict POIs with guaranteed error rates.
First, we propose a multi-objective optimization algorithm to find individuals who are expected to become stars in the future (rising stars), considering dynamic network data and multiple data types. Our algorithm outperforms the state of the art algorithm to find rising stars in academic data.
Second, we propose two algorithms to collect data in a network crawling setting to locate POIs in dark networks. We consider potential errors that adversarial POIs can introduce to data collection process to hinder the analysis. We test and present our results on several real-world networks, and show that the proposed algorithms achieve up to a 340% improvement over the next best strategy.
Next,We introduce the Adversarial Social Network Analysis game framework to model adversarial behavior of POIs towards a data collector in social networks. We run behavior experiments in Amazon Mechanical Turk and demonstrate the validity of the framework to study adversarial behavior by showing, 1) Participants understand their role, 2) Participants understand their objective in a game and, 3) Participants act as members of the adversarial group.
Last, we show that node classification algorithms can be used to predict POIs in social networks. We then demonstrate how to utilize conformal prediction framework [103] to obtain guaranteed error bounds in POI prediction. Experimental results show that the Conformal Prediction framework can provide up to a 30% improvement in node classification algorithm accuracy while maintaining guaranteed error bounds on predictions
The role of mentorship in protege performance
The role of mentorship on protege performance is a matter of importance to
academic, business, and governmental organizations. While the benefits of
mentorship for proteges, mentors and their organizations are apparent, the
extent to which proteges mimic their mentors' career choices and acquire their
mentorship skills is unclear. Here, we investigate one aspect of mentor
emulation by studying mentorship fecundity---the number of proteges a mentor
trains---with data from the Mathematics Genealogy Project, which tracks the
mentorship record of thousands of mathematicians over several centuries. We
demonstrate that fecundity among academic mathematicians is correlated with
other measures of academic success. We also find that the average fecundity of
mentors remains stable over 60 years of recorded mentorship. We further uncover
three significant correlations in mentorship fecundity. First, mentors with
small mentorship fecundity train proteges that go on to have a 37% larger than
expected mentorship fecundity. Second, in the first third of their career,
mentors with large fecundity train proteges that go on to have a 29% larger
than expected fecundity. Finally, in the last third of their career, mentors
with large fecundity train proteges that go on to have a 31% smaller than
expected fecundity.Comment: 23 pages double-spaced, 4 figure
Kinematics, Abundances, and Origin of Brightest Cluster Galaxies
We present kinematic parameters and absorption line strengths for three
brightest cluster galaxies, NGC 6166, NGC 6173 and NGC 6086. We find that NGC
6166 has a velocity dispersion profile which rises beyond 20 arcsec from the
nucleus, with a halo velocity dispersion in excess of 400 km/s. All three
galaxies show a positive and constant h4 Hermite moment. The rising velocity
dispersion profile in NGC 6166 thus indicates an increasing mass-to-light
ratio. Rotation is low in all three galaxies, and NGC 6173 and NGC 6086 show
possible kinematically decoupled cores. All three galaxies have Mg2 gradients
similar to those found in normal bright ellipticals, which are not steep enough
to support simple dissipative collapse models, but these could be accompanied
by dissipationless mergers which would tend to dilute the abundance gradients.
The [Mg/Fe] ratios in NGC 6166 and NGC 6086 are higher than that in NGC 6173,
and if NGC 6173 is typical of normal bright ellipticals, this suggests that cDs
cannot form from late mergers of normal galaxies.Comment: 21 pages, accepted for publication in MNRA
The Astronomy of the Kamilaroi People and their Neighbours
The Kamilaroi people and their neighbours, the Euahlayi, Ngemba, and
Murrawarri, are an Aboriginal cultural grouping located in the northwest and
north central of New South Wales. They have a rich history, but have been
missed in much of the literature concerned with sky knowledge in culture. This
study collected stories, some of which have not previously been reported in an
academic format, from Aboriginal people practicing their culture, augmented
with stories from the literature, and analysed the data to create a database of
sky knowledge that will be added to the larger body of Aboriginal cultural
knowledge in Australia. We found that there is a strong sky culture reflected
in the stories, and we also explored the stories for evidence of an
ethnoscientific approach to knowledge of the sky.Comment: 28 pages, 9 figure
Rexplore: unveiling the dynamics of scholarly data
Rexplore is a novel system that integrates semantic technologies, data mining techniques, and visual analytics to provide an innovative environment for making sense of scholarly data. Its functionalities include: i) a variety of views to make sense of important trends in research; ii) a novel semantic approach for characterising research topics; iii) a very fine-grained expert search with detailed multi-dimensional parameters; iv) an innovative graph view to relate a variety of academic entities; iv) the ability to detect and explore the main communities within a research topic; v) the ability to analyse research performance at different levels of abstraction, including individual researchers, organizations, countries, and research communities
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