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Vicente, P. (2023). Sampling Twitter users for social science research: Evidence from a systematic review of the literature. Quality and Quantity. 57 (6), 5449-5489

P. A. Duarte,  "Sampling Twitter users for social science research: Evidence from a systematic review of the literature", in Quality and Quantity, vol. 57, no. 6, pp. 5449-5489, 2023

@article{duarte2023_1734886018563,
	author = "Vicente, P.",
	title = "Sampling Twitter users for social science research: Evidence from a systematic review of the literature",
	journal = "Quality and Quantity",
	year = "2023",
	volume = "57",
	number = "6",
	doi = "10.1007/s11135-023-01615-w",
	pages = "5449-5489",
	url = "https://link.springer.com/article/10.1007/s11135-023-01615-w"
}

TY  - JOUR
TI  - Sampling Twitter users for social science research: Evidence from a systematic review of the literature
T2  - Quality and Quantity
VL  - 57
IS  - 6
AU  - Vicente, P.
PY  - 2023
SP  - 5449-5489
SN  - 0033-5177
DO  - 10.1007/s11135-023-01615-w
UR  - https://link.springer.com/article/10.1007/s11135-023-01615-w
AB  - All social media platforms can be used to conduct social science research, but Twitter is
the most popular as it provides its data via several Application Programming Interfaces,
which allows qualitative and quantitative research to be conducted with its members. As
Twitter is a huge universe, both in number of users and amount of data, sampling is generally
required when using it for research purposes. Researchers only recently began to question
whether tweet-level sampling—in which the tweet is the sampling unit—should be
replaced by user-level sampling—in which the user is the sampling unit. The major rationale
for this shift is that tweet-level sampling does not consider the fact that some core discussants
on Twitter are much more active tweeters than other less active users, thus causing
a sample biased towards the more active users. The knowledge on how to select representative
samples of users in the Twitterverse is still insufficient despite its relevance for reliable
and valid research outcomes. This paper contributes to this topic by presenting a systematic
quantitative literature review of sampling plans designed and executed in the context of
social science research in Twitter, including: (1) the definition of the target populations,
(2) the sampling frames used to support sample selection, (3) the sampling methods used
to obtain samples of Twitter users, (4) how data is collected from Twitter users, (5) the size
of the samples, and (6) how research validity is addressed. This review can be a methodological
guide for professionals and academics who want to conduct social science research
involving Twitter users and the Twitterverse.
ER  -