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Who's Tweeting About the President? What Big Survey Data Can Tell Us About Digital Traces?
[journal article]
Abstract Researchers hoping to make inferences about social phenomena using social media data need to answer two critical questions: What is it that a given social media metric tells us? And who does it tell us about? Drawing from prior work on these questions, we examine whether Twitter sentiment about Bara... view more
Researchers hoping to make inferences about social phenomena using social media data need to answer two critical questions: What is it that a given social media metric tells us? And who does it tell us about? Drawing from prior work on these questions, we examine whether Twitter sentiment about Barack Obama tells us about Americans' attitudes toward the president, the attitudes of particular subsets of individuals, or something else entirely. Specifically, using large-scale survey data, this study assesses how patterns of approval among population subgroups compare to tweets about the president. The findings paint a complex picture of the utility of digital traces. Although attention to subgroups improves the extent to which survey and Twitter data can yield similar conclusions, the results also indicate that sentiment surrounding tweets about the president is no proxy for presidential approval. Instead, after adjusting for demographics, these two metrics tell similar macroscale, long-term stories about presidential approval but very different stories at a more granular level and over shorter time periods.... view less
Keywords
social media; twitter; political attitude; public opinion; data capture; survey research
Classification
Interactive, electronic Media
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods
Free Keywords
Twitter sentiment; demographics; presidential approval; trends over time
Document language
English
Publication Year
2020
Page/Pages
p. 633-650
Journal
Social Science Computer Review, 38 (2020) 5
Issue topic
Integrating Survey Data and Digital Trace Data
DOI
https://doi.org/10.1177/0894439318822007
ISSN
1552-8286
Status
Published Version; peer reviewed
Licence
Deposit Licence - No Redistribution, No Modifications