@book{yin84, abstract = {This new edition of the best-selling Case Study Research has been carefully revised, updated, and expanded while retaining virtually all of the features and coverage of the Second Edition. Robert Yin's comprehensive presentation covers all aspects of the case study method--from problem definition, design, and data collection, to data analysis and composition and reporting. Yin also traces the uses and importance of case studies to a wide range of disciplines, from sociology, psychology and history to management, planning, social work, and education.}, address = {Beverly Hills, CA}, author = {Yin, Robert K.}, interhash = {7f654abb2607cf3459fd90f618fb1cec}, intrahash = {b4779f97dcab4a29935e5b9a36b4398b}, publisher = {Sage Publications}, series = {Applied social research methods series}, title = {Case Study Research: Design and Methods}, url = {http://www.amazon.ca/gp/product/0761925538/ref=wl_it_dp/702-0885532-1303250?ie=UTF8&coliid=I1NIZV3GVL8OUS&colid=1DVGN4EKR6AVM}, year = 1984 } @misc{Cattuto2006, abstract = {Collaborative tagging has been quickly gaining ground because of its ability to recruit the activity of web users into effectively organizing and sharing vast amounts of information. Here we collect data from a popular system and investigate the statistical properties of tag co-occurrence. We introduce a stochastic model of user behavior embodying two main aspects of collaborative tagging: (i) a frequency-bias mechanism related to the idea that users are exposed to each other's tagging activity; (ii) a notion of memory - or aging of resources - in the form of a heavy-tailed access to the past state of the system. Remarkably, our simple modeling is able to account quantitatively for the observed experimental features, with a surprisingly high accuracy. This points in the direction of a universal behavior of users, who - despite the complexity of their own cognitive processes and the uncoordinated and selfish nature of their tagging activity - appear to follow simple activity patterns.}, author = {Cattuto, Ciro and Loreto, Vittorio and Pietronero, Luciano}, citeulike-article-id = {695889}, eprint = {cs/0605015}, interhash = {59b1bd0ed96f41d2c3c98ff232df5dd2}, intrahash = {8d265ea13915a79ec08fe13b8e7074c7}, month = May, note = {{\tt arXiv:cs.CY/0605015}}, priority = {3}, title = {Collaborative Tagging and Semiotic Dynamics}, url = {http://arxiv.org/abs/cs/0605015}, year = 2006 } @inproceedings{1271658, abstract = {Bibliometric analysis is used as a measuring activity technique for basic research. There are many country level analyses of trends in scientific publications. These analyses give us an understanding of the macro-scale character of scientific activities. However, it is difficult to capture the qualitative evolution of scientific activities through them. In this regard, a meso-scale analysis of science activities, i.e., analysis of "research areas", is suitable for grasping qualitative changes in scientific activities. In this study, we develop a new method for mapping science at the research area level. Our method consists of two parts: constructing research areas from scientific publications and content analysis by experts. Research areas are explored through a co-citation analysis, and a map of science was generated to analyze how research areas relate to each other. This method contributes to endeavours to understand and track the changing nature of science.}, address = {Washington, DC, USA}, author = {SAKA, Ayaka and IGAMI, Masatsura}, booktitle = {IV '07: Proceedings of the 11th International Conference Information Visualization}, doi = {http://dx.doi.org/10.1109/IV.2007.77}, interhash = {1586085e24335ab7d0f8f5530d32552d}, intrahash = {a9168950512836c2155af1ed6dc99453}, isbn = {0-7695-2900-3}, pages = {453--458}, publisher = {IEEE Computer Society}, title = {Mapping Modern Science Using Co-citation Analysis}, url = {http://portal.acm.org/citation.cfm?id=1270398.1271658}, year = 2007 }