Makhortykh, Mykola; Urman, Aleksandra; Roberto, Ulloa (2020). How search engines disseminate information about COVID-19 and why they should do better. The Harvard Kennedy School (HKS) Misinformation Review, 1 10.37016/mr-2020-017
|
Text
IPeditsMykola-Makhortykh_Final.pdf - Published Version Available under License Creative Commons: Attribution (CC-BY). Download (913kB) | Preview |
Access to accurate and up-to-date information is essential for individual and collective decision making, especially at times of emergency. On February 26, 2020, two weeks before the World Health Organization (WHO) officially declared the COVID-19’s emergency a “pandemic,” we systematically collected and analyzed search results for the term “coronavirus” in three languages from six search engines. We found that different search engines prioritize specific categories of information sources, such as government-related websites or alternative media. We also observed that source ranking within the same search engine is subjected to randomization, which can result in unequal access to information among users.
Item Type: |
Journal Article (Original Article) |
|---|---|
Division/Institute: |
03 Faculty of Business, Economics and Social Sciences > Social Sciences > Institute of Communication and Media Studies (ICMB) |
UniBE Contributor: |
Makhortykh, Mykola, Urman, Aleksandra |
Subjects: |
000 Computer science, knowledge & systems 300 Social sciences, sociology & anthropology |
Language: |
English |
Submitter: |
Mykola Makhortykh |
Date Deposited: |
24 Jun 2020 16:41 |
Last Modified: |
05 Dec 2022 15:38 |
Publisher DOI: |
10.37016/mr-2020-017 |
Additional Information: |
Special Issue on COVID-19 and Misinformation |
Uncontrolled Keywords: |
algorithms, misinformation, search engines, bias, COVID-19, coronavirus |
BORIS DOI: |
10.7892/boris.144113 |
URI: |
https://boris.unibe.ch/id/eprint/144113 |
Actions (login required)
 |
Edit item |