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This is the training data used to produce the results shown in the paper listed below. Source: Sampled public tweets from Twitter streaming API. Date range: September 14 to October 27, 2010. Contains: data.arff: holds the un-resampled training data. data_balanced.arff: holds the resampled training data. data.instance_to_id.pickle: holds a Python pickle relating instance IDs in the data.arff file with Meme IDs in the Truthy database. To view the page for a particular meme ID, go to http://truthy.indiana.edu/m?id= Please cite: Jacob Ratkiewicz, Michael Conover, Mark Meiss, Bruno Goncalves, Alessandro Flammini, and Filippo Menczer. Detecting and Tracking Political Abuse in Social Media. Proc. 5th International AAAI Conference on Weblogs and Social Media ICWSM, 2011.
Twitter Data
Twitter Data
| 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 |
| views | 71 | |
| downloads | 4 |

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Downloads provided by UsageCounts