Temporal and textual analysis of social media on collective discourses during the Zika virus pandemic

Abstract

Background: While existing studies have investigated the role of social media on health-related communication, little is known about the potential differences between different users groups on different social media platforms in responses to a health event. This study sets out to explore the online discourse of governmental authorities and the public in Singapore during the recent Zika pandemic in 2016.

Methods: Social media data were extracted from Facebook and Twitter using retroactive keyword sourcing of the word "Zika" to search for posts and a location filter of "Singapore". Government posts, public posts, and replies to these original posts were included in the temporal and textual analysis.

Results: Overall, Facebook contained more government and individual content whereas Twitter had more content from news media accounts. Though the relative volume of Zika content from different data sources paralleled the peaks and troughs of Zika activities across time, discourses from different data sources differed in their temporal patterns, such that the public discourse died down faster than the government discourse after the outbreak was declared. In addition, the content of discourses differed among data sources. While government discourse included factual information of the disease, public discourse contained more elements of care such as worry about the risks to pregnant women, and elements of community such as well-wishes to each other.

Conclusions: Our study demonstrates the temporal and content differences between user groups and social media platforms in social media conversations during the Zika pandemic. It suggests that future research should examine the collective discourse of a health event by investigating social media discourses within varied sources rather than focusing on a singular social media platform and by one particular type of users.

Keywords: Facebook; Health communication; Public health; Social media; Twitter; Zika.

Fig. 1

The relative frequency of discourses about Zika from 1 October 2015 to 31 December 2016, with reference to Zika confirmed cases. [Note: To plot all figures on a common scale, figures were scaled to the highest peaks for each data source, respectively. The peak was assigned a score of 100. FBGOVT-POST = Facebook government posts; FBGOVT-REPLIES = public replies to Facebook government posts; FBPUBLIC-POST = Facebook public posts; FBPUBLIC-REPLIES = public replies to Facebook public posts; TWGOVT-TWEET = Twitter government tweets; TWPUBLIC-TWEET = Twitter public tweets]

Fig. 2

The relative frequency of discourses about Zika from 1 October 2015 to 31 December 2016 by different social media handles. [Note: To plot all figures on a common scale, figures were scaled to the highest peaks for each data source, respectively. The peak was assigned a score of 100. FB = Facebook; TW = Twitter. FB/TW-COMPANY = Facebook posts/Tweets published by companies or communities; FB/TW-OTHER GOV = Facebook posts/Tweets published by other governments except the MOH, NEA, and HPB; FB/TW-INDIVIDUALS = Facebook posts/tweets published by individual users; FB/TW-NEWS = Facebook posts/tweets published by news agencies]

Fig. 3

Comparison between narratives of Zika-only, dengue-only, and both, on Facebook (the upper panel) and Twitter (the lower panel)

Fig. 4

Word clouds of the most frequently used words during the 2016 Zika outbreak in Singapore across data sources (a-f). [Note: All words were lemmatized before analysis. The search word “Zika” and location “Singapore” were removed from display. The size of words indicates its relative frequency, where words in larger fonts were more frequently used]