Replication data for: "Testing Propositions Derived from Twitter Studies: Generalization and Replication in Computational Social Science"
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下载链接:
https://doi.org/10.7910/DVN/L1MJZ6
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资源简介:
Replication is an essential requirement for scientific discovery. The current study aims to generalize and replicate 10 propositions made in previous Twitter studies using a representative dataset. Our findings suggest 6 out of 10 propositions could not be replicated due to the variations of data collection, analytic strategies employed and inconsistent measurements. The replication data include 4 files: 1. EgoAlterProfiles (egos are randomly selected Twitter users; alters are the followers and followees of the egos) 2. EgoNetworks (all egos and their following relationships with alters) 3. Exposure (the aggregated data for testing exposure hypothesis) 4. EgoTimelines (all tweets information posted by egos) All datasets have been anonymized.
创建时间:
2018-07-07



