@article{an2004characterizing,
  abstract = {Citation graphs representing a body of scientific literature convey measures of scholarly activity and productivity. In this work we present a study of the structure of the citation graph of the computer science literature. Using a web robot we built several topic-specific citation graphs and their union graph from the digital library ResearchIndex. After verifying that the degree distributions follow a power law, we applied a series of graph theoretical algorithms to elicit an aggregate picture of the citation graph in terms of its connectivity. We discovered the existence of a single large weakly-connected and a single large biconnected component, and confirmed the expected lack of a large strongly-connected component. The large components remained even after removing the strongest authority nodes or the strongest hub nodes, indicating that such tight connectivity is widespread and does not depend on a small subset of important nodes. Finally, minimum cuts between authority papers of different areas did not result in a balanced partitioning of the graph into areas, pointing to the need for more sophisticated algorithms for clustering the graph.},
  acmid = {1031388},
  address = {London},
  author = {An, Yuan and Janssen, Jeannette and Milios, Evangelos E.},
  doi = {10.1007/s10115-003-0128-3},
  interhash = {73fdd0592c1641d05da5d2323d9f59ae},
  intrahash = {2fe1a8e5fdeb537973491ad334acb0ea},
  issn = {0219-1377},
  issue = {6},
  journal = {Knowledge and Information Systems},
  month = nov,
  number = 6,
  numpages = {15},
  pages = {664--678},
  publisher = {Springer},
  title = {Characterizing and Mining the Citation Graph of the Computer Science Literature},
  url = {http://dx.doi.org/10.1007/s10115-003-0128-3},
  volume = 6,
  year = 2004
}

@inproceedings{angelova2008characterizing,
  abstract = {Social networks and collaborative tagging systems are rapidly gaining popularity as a primary means for storing and sharing data among friends, family, colleagues, or perfect strangers as long as they have common interests. del.icio.us is a social network where people store and share their personal bookmarks. Most importantly, users tag their bookmarks for ease of information dissemination and later look up. However, it is the friendship links, that make delicious a social network. They exist independently of the set of bookmarks that belong to the users and have no relation to the tags typically assigned to the bookmarks. To study the interaction among users, the strength of the existing links and their hidden meaning, we introduce implicit links in the network. These links connect only highly "similar" users. Here, similarity can reflect different aspects of the user’s profile that makes her similar to any other user, such as number of shared bookmarks, or similarity of their tags clouds. We investigate the question whether friends have common interests, we gain additional insights on the strategies that users use to assign tags to their bookmarks, and we demonstrate that the graphs formed by implicit links have unique properties differing from binomial random graphs or random graphs with an expected power-law degree distribution. },
  author = {Angelova, Ralitsa and Lipczak, Marek and Milios, Evangelos and Prałat, Paweł},
  booktitle = {Proceedings of the Mining Social Data Workshop (MSoDa)},
  interhash = {f74d27a66d2754f3d5892d68c4abee4c},
  intrahash = {02d6739886a13180dd92fbb7243ab58b},
  month = jul,
  organization = {ECAI 2008},
  pages = {21--25},
  title = {Characterizing a social bookmarking and tagging network},
  url = {http://www.math.ryerson.ca/~pralat/papers/2008_delicious.pdf},
  year = 2008
}