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This is the evaluation data for this paper: https://arxiv.org/abs/1804.06701 The analysis scripts for this data, as well as a brief explanation on what's what can be found here: https://github.com/VeReMi-dataset/VeReMi-popper/tree/master/analysis This data was directly derived from the VeReMI dataset. Because the derivation scripts run on a cluster and are quite closely tied to that cluster, we decided to also publish the raw data. For processing, I split the data into 3 groups (low, medium, and high) of 75 tgz files that correspond to different densities (see paper for details). Basically this corresponds to A_R0_* to A_R14_*, A_R15_* to A_R29_* and A_R30_ to A_R44_* (this can also be clearly seen by the file size). If you store these in ./low, ./med, ./high respectively, you'll end up with the same graphs as published here: https://github.com/vs-uulm/securecomm2018-misbehavior-evaluation For the paper, we used a sub-set of these graphs.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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