Work

Testing Propositions Derived from Twitter Studies: Generalization and Replication in Computational Social Science

Year: 2015

Type: article

Abstract: 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 study's contributions are twofold: First, it systematically summarized and assessed some important claims in the field, which can inform future studies. Second, it proposed a feasible approach to generating a random sample of Twitter users and its associated ego networks, which might serve as a solution for answering social-scientific questions at the individual level without accessing the complete data archive.

Source: PLoS ONE

DOI: 10.1371/journal.pone.0134270

Authors: Hai Liang, King-wa Fu

Institution: University of Hong Kong

Language: English

Topic: Computational and Text Analysis Methods

Subfield: General Social Sciences

Field: Social Sciences

Domain: Social Sciences

Open Access status: gold

Estimated APC paid: $2,382

Funders: University of Hong Kong, Hong Kong Government