Going beyond fact-checking to fight health misinformation: A multi-level analysis of the Twitter response to health news stories

被引：14

作者：

Zhong, Bu ^{[1
]}

机构：

[1] Hong Kong Baptist Univ, Sch Journalism, Dept Interact Media, Kowloon Tong, 5 Hereford Rd,CVA 804,Lee Shau Kee Commun Bldg, Hong Kong, Peoples R China

来源：

INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT | 2023年 / 70卷

关键词：

Health misinformation; Health news; Information quality; Source credibility; Tweet; Sentiment analysis; FAKE NEWS; INFORMATION; SPREAD;

D O I：

10.1016/j.ijinfomgt.2023.102626

中图分类号：

G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];

学科分类号：

1205 ; 120501 ;

摘要：

Health misinformation has become an unfortunate truism of social media platforms, where lies could spread faster than truth. Despite considerable work devoted to suppressing fake news, health misinformation, including low-quality health news, persists and even increases in recent years. One promising approach to fighting bad information is studying the temporal and sentiment effects of health news stories and how they are discussed and disseminated on social media platforms like Twitter. As part of the effort of searching for innovative ways to fight health misinformation, this study analyzes a dataset of more than 1600 objectively and independently reviewed health news stories published over a 10-year span and nearly 50,000 Twitter posts responding to them. Specifically, it examines the source credibility of health news circulated on Twitter and the temporal, sentiment features of the tweets containing or responding to the health news reports. The results show that health news stories that are rated low by experts are discussed more, persist longer, and produce stronger sentiments than highly rated ones in the tweetosphere. However, the highly rated stories retained a fresh interest in the form of new tweets for a longer period. An in-depth understanding of the characteristics of health news distribution and discussion is the first step toward mitigating the surge of health misinformation. The findings provide insights into understanding the mechanism of health information dissemination on social media and practical implications to fight and mitigate health misinformation on digital media platforms.

引用

页数：11

共 64 条

[41] Why do people believe health misinformation and who is at risk? A systematic review of individual differences in susceptibility to health misinformation [J].

Nan, Xiaoli ;

Wang, Yuan ;

Thier, Kathryn .

SOCIAL SCIENCE & MEDICINE, 2022, 314

[42]

Nickerson R. S., 1998, REV GEN PSYCHOL, V2, P175, DOI [DOI 10.1037/1089-2680.2.2.175, 10.1037/1089-2680.2.2.175]

[43]

NIH, 2011, EV HLTH INF INT QUES

[44] Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries [J].

Olteanu, Alexandra ;

Castillo, Carlos ;

Diaz, Fernando ;

Kiciman, Emre .

FRONTIERS IN BIG DATA, 2019, 2

[45]

Posetti J., 2020, DISINFODEMIC DECIPHE, P1

[46] A New Application of Social Impact in Social Media for Overcoming Fake News in Health [J].

Pulido, Cristina M. ;

Ruiz-Eugenio, Laura ;

Redondo-Sama, Gisela ;

Villarejo-Carballido, Beatriz .

INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2020, 17 (07)

[47] Understanding the efficiency of social media based crisis communication during hurricane Sandy [J].

Roy, Kamol Chandra ;

Hasan, Samiul ;

Sadri, Arif Mohaimin ;

Cebrian, Manuel .

INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT, 2020, 52

[48] How do US journalists cover treatments, tests, products, and procedures? An evaluation of 500 stories [J].

Schwitzer, Gary .

PLOS MEDICINE, 2008, 5 (05) :700-704

[49] Effect of Hydroxychloroquine on Clinical Status at 14 Days in Hospitalized Patients With COVID-19 A Randomized Clinical Trial [J].

Self, Wesley H. ;

Semler, Matthew W. ;

Leither, Lindsay M. ;

Casey, Jonathan D. ;

Angus, Derek C. ;

Brower, Roy G. ;

Chang, Steven Y. ;

Collins, Sean P. ;

Eppensteiner, John C. ;

Filbin, Michael R. ;

Files, D. Clark ;

Gibbs, Kevin W. ;

Ginde, Adit A. ;

Gong, Michelle N. ;

Harrell, Frank E. ;

Hayden, Douglas L. ;

Hough, Catherine L. ;

Johnson, Nicholas J. ;

Khan, Akram ;

Lindsell, Christopher J. ;

Matthay, Michael A. ;

Moss, Marc ;

Park, Pauline K. ;

Rice, Todd W. ;

Robinson, Bryce R. H. ;

Schoenfeld, David A. ;

Shapiro, Nathan, I ;

Steingrub, Jay S. ;

Ulysse, Christine A. ;

Weissman, Alexandra ;

Yealy, Donald M. ;

Thompson, B. Taylor ;

Brown, Samuel M. .

JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 2020, 324 (21) :2165-2176

[50] Linguistic signals under misinformation and fact-checking: Evidence from user comments on social media [J].

Jiang, Shan ;

Wilson, Christo .

Proceedings of the ACM on Human-Computer Interaction, 2018, 2 (CSCW)

← 1 2 3 4 5 6 7 →