@book{lem2003sterntagebuecher,
  author = {Lem, Stanislaw},
  interhash = {b2dd2031126ec37b8d1bc6323092eba8},
  intrahash = {7e515f1c110866e81365d2bc62f3e227},
  publisher = {Suhrkamp},
  title = {Sterntagebücher},
  url = {http://www.amazon.de/exec/obidos/ASIN/3518455346/},
  year = 2003
}

@book{knuth1989concrete,
  address = {Reading},
  author = {Graham, Ronald L. and Knuth, Donald E. and Patashnik, Oren},
  interhash = {a1450d7bb87f0107150d43a314a88326},
  intrahash = {ccef670ef39186763ecd379d2cca1e0a},
  publisher = {Addison-Wesley},
  title = {Concrete Mathematics: A Foundation for Computer Science},
  year = 1989
}

@booklet{nn2011article,
  author = {N.N.},
  howpublished = {Brochure},
  interhash = {f4c36889c40205600542b11c4d3b153e},
  intrahash = {3da1baac19bc69f7b31a59098e0c20a8},
  title = {How To Get Your Article Published},
  year = 2011
}

@article{newman2001structure,
  abstract = {The structure of scientific collaboration networks is investigated. Two scientists are considered connected if they have authored a paper together and explicit networks of such connections are constructed by using data drawn from a number of databases, including MEDLINE biomedical research, the Los Alamos e-Print Archive physics, and NCSTRL computer science. I show that these collaboration networks form  ” small worlds,” in which randomly chosen pairs of scientists are typically separated by only a short path of intermediate acquaintances. I further give results for mean and distribution of numbers of collaborators of authors, demonstrate the presence of clustering in the networks, and highlight a number of apparent differences in the patterns of collaboration between the fields studied.},
  author = {Newman, M. E. J.},
  doi = {10.1073/pnas.98.2.404},
  eprint = {http://www.pnas.org/content/98/2/404.full.pdf+html},
  interhash = {8c5edd915b304ae09fc08e0a51dfd5e9},
  intrahash = {a4d3149c7198762a99102935da4d1bdb},
  journal = {Proceedings of the National Academy of Sciences},
  number = 2,
  pages = {404--409},
  title = {The structure of scientific collaboration networks},
  url = {http://www.pnas.org/content/98/2/404.abstract},
  volume = 98,
  year = 2001
}

@article{bollen2009clickstream,
  abstract = {Background  Intricate maps of science have been created from citation data to visualize the structure of scientific activity. However, most scientific publications are now accessed online. Scholarly web portals record detailed log data at a scale that exceeds the number of all existing citations combined. Such log data is recorded immediately upon publication and keeps track of the sequences of user requests (clickstreams) that are issued by a variety of users across many different domains. Given these advantages of log datasets over citation data, we investigate whether they can produce high-resolution, more current maps of science.  Methodology  Over the course of 2007 and 2008, we collected nearly 1 billion user interactions recorded by the scholarly web portals of some of the most significant publishers, aggregators and institutional consortia. The resulting reference data set covers a significant part of world-wide use of scholarly web portals in 2006, and provides a balanced coverage of the humanities, social sciences, and natural sciences. A journal clickstream model, i.e. a first-order Markov chain, was extracted from the sequences of user interactions in the logs. The clickstream model was validated by comparing it to the Getty Research Institute's Architecture and Art Thesaurus. The resulting model was visualized as a journal network that outlines the relationships between various scientific domains and clarifies the connection of the social sciences and humanities to the natural sciences.   Conclusions  Maps of science resulting from large-scale clickstream data provide a detailed, contemporary view of scientific activity and correct the underrepresentation of the social sciences and humanities that is commonly found in citation data.},
  author = {Bollen, Johan and van de Sompel, Herbert and Hagberg, Aric and Bettencourt, Luis and Chute, Ryan and Rodriguez, Marko A. and Balakireva, Lyudmila},
  doi = {10.1371/journal.pone.0004803},
  interhash = {3a371a1ed31d14204770315b52023b96},
  intrahash = {e61bd0c26cc1c08cff22a8301d03044f},
  journal = {PLoS ONE},
  month = mar,
  number = 3,
  pages = {e4803},
  publisher = {Public Library of Science},
  title = {Clickstream Data Yields High-Resolution Maps of Science},
  url = {http://dx.doi.org/10.1371/journal.pone.0004803},
  volume = 4,
  year = 2009
}