ia-reality-call (Dynamic Networks)
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Metadata
| Category | Sparse networks, temporal networks |
| Collection | Interaction networks |
| Tags | |
| Source | http://realitycommons.media.mit.edu/realitymining.html |
| Short | user-calls-user |
| Vertex type | Person |
| Edge type | Call |
| Format | Undirected |
| Edge weights | Multiple unweighted edges |
| Metadata | Time (edges have timestamps) |
| Description | Reality mining network data consists of human mobile phone call events between a small set of core users at the Massachusetts Institute of Technology (MIT) whom actually were assigned mobile phones for which all calls were collected. The data also contains calls from users outside this small set of users to other phones of individuals that were not actively monitored and thus these nodes generally have fewer edges than nodes within the small set of users at MIT that participated in the experiment and were assigned phones. The data was collected collected by the Reality Mining experiment performed in 2004 as part of the Reality Commons project. The data was collected over 9 months using 100 mobile phones. A node represents a person; an edge indicates a phone call or voicemail between two users. See http://realitycommons.media.mit.edu/realitymining.html for more details. |
Please cite the following if you use the data:
Note that if you transform/preprocess the data, please consider sharing the data by uploading it along with the details on the transformation and reference to any published materials using it.
@inproceedings{nr,
title={The Network Data Repository with Interactive Graph Analytics and Visualization},
author={Ryan A. Rossi and Nesreen K. Ahmed},
booktitle={AAAI},
url={https://networkrepository.com},
year={2015}
}
@article{eagle2006reality,
title={Reality mining: sensing complex social systems},
author={Eagle, N. and Pentland, A.},
journal={Personal and Ubiquitous Computing},
volume={10},
number={4},
pages={255--268},
year={2006},
}
Network Statistics
| Nodes | 6.8K |
| Edges | 51.2K |
| Density | 0.00221103 |
| Maximum degree | 3K |
| Minimum degree | 1 |
| Average degree | 15 |
| Assortativity | -0.315687 |
| Number of triangles | 923.7K |
| Average number of triangles | 135 |
| Maximum number of triangles | 97.3K |
| Average clustering coefficient | 0.362203 |
| Fraction of closed triangles | 0.0299949 |
| Maximum k-core | 967 |
| Lower bound of Maximum Clique | 116 |
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