Semantic Scholar Open Access 2019 1457 sitasi

Fake news on Twitter during the 2016 U.S. presidential election

Nir Grinberg K. Joseph Lisa Friedland B. Swire‐Thompson D. Lazer

Abstrak

Finding facts about fake news There was a proliferation of fake news during the 2016 election cycle. Grinberg et al. analyzed Twitter data by matching Twitter accounts to specific voters to determine who was exposed to fake news, who spread fake news, and how fake news interacted with factual news (see the Perspective by Ruths). Fake news accounted for nearly 6% of all news consumption, but it was heavily concentrated—only 1% of users were exposed to 80% of fake news, and 0.1% of users were responsible for sharing 80% of fake news. Interestingly, fake news was most concentrated among conservative voters. Science, this issue p. 374; see also p. 348 A small proportion of voters share and are exposed to the majority of online fake news. The spread of fake news on social media became a public concern in the United States after the 2016 presidential election. We examined exposure to and sharing of fake news by registered voters on Twitter and found that engagement with fake news sources was extremely concentrated. Only 1% of individuals accounted for 80% of fake news source exposures, and 0.1% accounted for nearly 80% of fake news sources shared. Individuals most likely to engage with fake news sources were conservative leaning, older, and highly engaged with political news. A cluster of fake news sources shared overlapping audiences on the extreme right, but for people across the political spectrum, most political news exposure still came from mainstream media outlets.

Topik & Kata Kunci

Penulis (5)

N

Nir Grinberg

K

K. Joseph

L

Lisa Friedland

B

B. Swire‐Thompson

D

D. Lazer

Format Sitasi

Grinberg, N., Joseph, K., Friedland, L., Swire‐Thompson, B., Lazer, D. (2019). Fake news on Twitter during the 2016 U.S. presidential election. https://doi.org/10.1126/science.aau2706

Akses Cepat

Lihat di Sumber doi.org/10.1126/science.aau2706
Informasi Jurnal
Tahun Terbit
2019
Bahasa
en
Total Sitasi
1457×
Sumber Database
Semantic Scholar
DOI
10.1126/science.aau2706
Akses
Open Access ✓