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Using Multivariate Statistics

[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

Random graphs

Building Leadership Effectiveness This program encourages leaders to develop practices that transform values into action, vision into realities, obstacles into innovations, and risks into rewards. Participants will be introduced to the five practices of exemplary leadership: modeling the way, inspiring a shared vision, challenging the process, enabling others to act, and encouraging the heart Coaching & Communicating for Performance Coaching & Communicating for Performance is a highly interactive program that will give supervisors and managers the opportunity to build skills that will enable them to share expectations and set objectives for employees, provide constructive feedback, more effectively engage in learning conversations, and coaching opportunities. Skillful Conflict Management for Leaders As a leader, it is important to understand conflict and be effective at conflict management because the way conflict is resolved becomes an integral component of our university’s culture. This series of conflict management sessions help leaders learn and put into practice effective strategies for managing conflict.

기독교 사역과 Leadership

The power of feedback.

We analyzed over 33,000 financial operations involving an Italian factoring company.We present network construction techniques based on different risk factors.Social network metrics are an important addition to anti-money laundering.Cluster analysis on tacit link networks can help identify suspicious actors.Our models and metrics are easy to replicate and to integrate into existing systems. This research explores the opportunities for the application of network analytic techniques to prevent money laundering. We worked on real world data by analyzing the central database of a factoring company, mainly operating in Italy, over a period of 19 months. This database contained the financial operations linked to the factoring business, together with other useful information about the company clients.We propose a new approach to sort and map relational data and present predictive models - based on network metrics - to assess risk profiles of clients involved in the factoring business. We find that risk profiles can be predicted by using social network metrics. In our dataset, the most dangerous social actors deal with bigger or more frequent financial operations; they are more peripheral in the transactions network; they mediate transactions across different economic sectors and operate in riskier countries or Italian regions. Finally, to spot potential clusters of criminals, we propose a visual analysis of the tacit links existing among different companies who share the same owner or representative. Our findings show the importance of using a network-based approach when looking for suspicious financial operations and potential criminals.

Using social network analysis to prevent money laundering

Forecasting tourism demand has important implications for both policy makers and companies operating in the tourism industry. In this research, we applied methods and tools of social network and semantic analysis to study user-generated content retrieved from online communities which interacted on the TripAdvisor travel forum. We analyzed the forums of 7 major European capital cities, over a period of 10 years, collecting more than 2,660,000 posts, written by about 147,000 users. We present a new methodology of analysis of tourism-related big data and a set of variables which could be integrated into traditional forecasting models. We implemented Factor Augmented Autoregressive and Bridge models with social network and semantic variables which often led to a better forecasting performance than univariate models and models based on Google Trend data. Forum language complexity and the centralization of the communication network – i.e. the presence of eminent contributors – were the variables that contributed more to the forecasting of international airport arrivals.

Using social network and semantic analysis to analyze online travel forums and forecast tourism demand

The Semantic Brand Score

Purpose




The purpose of this paper is to identify the factors influencing the growth of healthcare virtual communities of practice (VCoPs) through a seven-year longitudinal study conducted using metrics from social-network and semantic analysis. By studying online communication along the three dimensions of social interactions (connectivity, interactivity and language use), the authors aim to provide VCoP managers with valuable insights to improve the success of their communities.




Design/methodology/approach




Communications over a period of seven years (April 2008 to April 2015) and between 14,000 members of 16 different healthcare VCoPs coexisting on the same web platform were analysed. Multilevel regression models were used to reveal the main determinants of community growth over time. Independent variables were derived from social network and semantic analysis measures.




Findings




Results show that structural and content-based variables predict the growth of the community. Progressively, more people will join a community if its structure is more centralised, leaders are more dynamic (they rotate more) and the language used in the posts is less complex.




Research limitations/implications




The available data set included one Web platform and a limited number of control variables. To consolidate the findings of the present study, the experiment should be replicated on other healthcare VCoPs.




Originality/value




The study provides useful recommendations for setting up and nurturing the growth of professional communities, considering, at the same time, the interaction patterns among the community members, the dynamic evolution of these interactions and the use of language. New analytical tools are presented, together with the use of innovative interaction metrics, that can significantly influence community growth, such as rotating leadership.

It is rotating leaders who build the swarm: social network determinants of growth for healthcare virtual communities of practice

Purpose – The purpose of this paper is to examine the innovative capabilities of biotech start-ups in relation to geographic proximity and knowledge sharing interaction in the R & D network of a major high-tech cluster. Design/methodology/approach – This study compares longitudinal informal communication networks of researchers at biotech start-ups with company patent applications in subsequent years. For a year, senior R & D staff members from over 70 biotech firms located in the Boston biotech cluster were polled and communication information about interaction with peers, universities and big pharmaceutical companies was collected, as well as their geolocation tags. Findings – Location influences the amount of communication between firms, but not their innovation success. Rather, what matters is communication intensity and recollection by others. In particular, there is evidence that rotating leadership – changing between a more active and passive communication style – is a predictor of innovative perfo...

Andrea Fronzetti Colladon

Papers

Using social network analysis to prevent money laundering

Using social network and semantic analysis to analyze online travel forums and forecast tourism demand

The Semantic Brand Score

It is rotating leaders who build the swarm: social network determinants of growth for healthcare virtual communities of practice

The power of reciprocal knowledge sharing relationships for startup success