Peter A. Gloor

Bio: Peter A. Gloor is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Social network analysis & Social network. The author has an hindex of 37, co-authored 211 publications receiving 4918 citations. Previous affiliations of Peter A. Gloor include University of Cologne & Union Bank of Switzerland.

The power of reciprocal knowledge sharing relationships for startup success

Abstract: 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...

Using four different online media sources to forecast the crude oil price

Abstract: This study looks for signals of economic awareness on online social media and tests their significance in economic predictions. The study analyses, over a period of 2 years, the relationship between the West Texas Intermediate daily crude oil price and multiple predictors extracted from Twitter; Google Trends; Wikipedia; and the Global Data on Events, Location and Tone (GDELT) database. Semantic analysis is applied to study the sentiment, emotionality and complexity of the language used. Autoregressive Integrated Moving Average with Explanatory Variable (ARIMAX) models are used to make predictions and to confirm the value of the study variables. Results show that the combined analysis of the four media platforms carries valuable information in making financial forecasting. Twitter language complexity, GDELT number of articles and Wikipedia page reads have the highest predictive power. This study also allows a comparison of the different fore-sighting abilities of each platform, in terms of how many days a...

Social capital increases efficiency of collaboration among Wikipedia editors

Abstract: In this study we measure the impact of pre-existing social capital on the efficiency of collaboration among Wikipedia editors. To construct a social network among Wikipedians we look to mutual interaction on the user talk pages of Wikipedia editors. As our data set, we analyze the communication networks associated with 3085 featured articles - the articles of highest quality in the English Wikipedia, comparing it to the networks of 80154 articles of lower quality. As the metric to assess the quality of collaboration, we measure the time of quality promotion from when an article is started until it is promoted to featured article. The study finds that the higher pre-existing social capital of editors working on an article is, the faster the articles they work on reach higher quality status, such as featured articles. The more cohesive and more centralized the collaboration network, and the more network members were already collaborating before starting to work together on an article, the faster the article they work on will be promoted or featured.

The Evolution of Interaction Networks in Massively Multiplayer Online Games

Abstract: This article examines the co-evolution of players’ individual performance and their interaction network in a Massively Multiplayer Online Game (MMOG). The objective is to test whether the application of theories from the real world is valid in virtual worlds. While the results indicate that the structural effects and demographic variables active in the real world influence the evolution of the players’ interaction network in MMOGs (e.g. transitivity, reciprocity, and homophily), they do not provide evidence that players’ structural embeddedness in the interaction network influences player performance. These findings have important implications for researchers and practitioners who need to understand social processes in MMOGs (e.g., when launching marketing campaigns in MMOGs) or who study MMOGs and then use their findings to draw conclusions about the real world (e.g., when analyzing the relationship between employee performance and network structure).

CYBERMAP: yet another way of navigating in hyperspace

Abstract: By integrating dynamic linking and automatic link generation into the automatic generation of an overview map we get a unique tool for navigation in hyperspace. We introduce the concept of HYPERDRAWERS to get a means for the partitioning of nodes in ordered sequences. CYBERMAP either complements existing navigational aids for hyperdocuments or provides a self sufficient navigation tool for browsing in a document. In addition CYBERMAP offers the capability of horizontal growth and easy hypertextualization of non-hypertextual documents without restricting the use of already installed browsing mechanisms besides CYBERMAP.

Using Multivariate Statistics

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Pattern Recognition and Machine Learning

Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Principles of Neural Science

Abstract: I have developed "tennis elbow" from lugging this book around the past four weeks, but it is worth the pain, the effort, and the aspirin. It is also worth the (relatively speaking) bargain price. Including appendixes, this book contains 894 pages of text. The entire panorama of the neural sciences is surveyed and examined, and it is comprehensive in its scope, from genomes to social behaviors. The editors explicitly state that the book is designed as "an introductory text for students of biology, behavior, and medicine," but it is hard to imagine any audience, interested in any fragment of neuroscience at any level of sophistication, that would not enjoy this book. The editors have done a masterful job of weaving together the biologic, the behavioral, and the clinical sciences into a single tapestry in which everyone from the molecular biologist to the practicing psychiatrist can find and appreciate his or

The knowledge-creating company : how Japanese companies create the dynamics of innovation

Abstract: How has Japan become a major economic power, a world leader in the automotive and electronics industries? What is the secret of their success? The consensus has been that, though the Japanese are not particularly innovative, they are exceptionally skilful at imitation, at improving products that already exist. But now two leading Japanese business experts, Ikujiro Nonaka and Hiro Takeuchi, turn this conventional wisdom on its head: Japanese firms are successful, they contend, precisely because they are innovative, because they create new knowledge and use it to produce successful products and technologies. Examining case studies drawn from such firms as Honda, Canon, Matsushita, NEC, 3M, GE, and the U.S. Marines, this book reveals how Japanese companies translate tacit to explicit knowledge and use it to produce new processes, products, and services.