Systematic Delineation of Media Polarity on COVID-19 Vaccines in Africa: Computational Linguistic Modeling Study

"...media communications can affect public perception and attitude toward medical treatment, vaccination, or subject matter, particularly when the population has limited knowledge on the subject."

Studies have shown that the degree of public acceptance of a medical intervention, particularly a vaccination programme, is an important factor in its success. Parallel to the emergence of the COVID-19 pandemic is the proliferation of information regarding the pandemic (an "infodemic"), which risks misleading the public, potentially affecting vaccine acceptance and uptake. This study attempts to systematically assess media communications (Google News headlines or snippets and Twitter posts) to understand prevailing sentiments regarding COVID-19 vaccines in Africa. The purpose is to guide health actors in creating informed relevant polices, as the continent was (as of this writing) awaiting the availability of viable vaccines to combat the pandemic.

Research questions included:

• What were the media activity patterns regarding COVID-19 vaccines in Africa within the study period of February 2 2020 to May 5 2020?
• What are the prevailing sentiments (i.e., positive, negative, or neutral) in the communications?
• How do the sentiment polarities in Twitter posts compare to those in Google News communications?
• How do the sentiment results from three different sentiment analysis approaches compare with each other?
• What specific activities or events might have triggered the prevailing emotions in the communications?

The researchers use sentiment analysis, which is a multidisciplinary field involved with machine learning and artificial intelligence. It is a subset of natural language processing concerned with the systematic extraction, analysis, classification, quantification, and interpretation of affective tonality, opinions, and subjective information in human communications (written or spoken) using computational linguistic methods to derive value of the opinions people express. One challenge of this methodology is that most of the sentiment analysis models and libraries are built in English, which limits their applicability. Thus, for this study, English-language keywords were used to query the data sources: "COVID-19 vaccine Africa", "COVID19 vaccine Africa", and "Coronavirus vaccine Africa". (This approach includes communications that have hashtags of the keywords).

Specifically, 637 Twitter posts and 569 Google News headlines or descriptions, retrieved between February 2 and May 5 2020, were analysed using three standard computational linguistics models: TextBlob, Valence Aware Dictionary for sEntiment Reasoning (VADER), and Word2Vec, combined with a bidirectional long short-term memory neural network.

The findings revealed that media activity on the subject matter was relatively low in the first 3 weeks of the study period (February 2-23 2020). because COVID-19 was just beginning to gain media attention in Africa during that time. There was a spike in media activity on both Twitter and Google News between March 29 and April 5 2020, with corresponding increases in negative sentiments based on results from TextBlob and VADER. This period coincides with negative public reception of the remarks made by 2 French medical doctors on COVID-19 testing in Africa that were deemed racist and ascribed to a "hangover from colonial mentality". Such patterns "reiterate the importance of knowledge and information consumption during the time of a medical emergency or crisis."

"Although there was a generally weak decline in positivity from both Twitter and Google News data across the study period, prevailing sentiments were neutral to positive. This gives an indication that generally truer and more evidence-based information regarding COVID-19 vaccines in Africa are circulating on Twitter and Google News as compared to falsehoods..." The researchers attribute these findings to sustained efforts by various media and health actors in ensuring the availability of factual information about the pandemic:

• "[D]eliberate and sustained efforts made on various media platforms like Twitter, Facebook, Google, Microsoft, Reddit, and others to limit the spread of misleading and potentially harmful content regarding the COVID-19 pandemic..." For example, Google put in place mechanisms to ensure that searches related to COVID-19 on the company's search engine triggered an "SOS Alert", with news from mainstream publications including the World Health Organization (WHO), National Public Radio, and the United States (US) Centers for Disease Control and Prevention (CDC) displayed prominently.
• Intensified efforts on the part of national and international entities and health actors to ensure accurate and reliable information to the public regarding COVID-19. For example, in response to skepticism regarding COVID-19 vaccines, Media Monitoring Africa, a media organisation that "aims to promote the development of critical, ethical, and a free and fair media culture in South Africa and the rest of the continent, triggered its Real411 platform, wherein the public can report disinformation regarding COVID-19 to a digital complaints committee...The platform was originally set up during the country's elections to enable reporting of objectionable speech by members of the public. This strategic media response was deemed necessary following a national survey conducted between April 15-23, 2020, among a representative sample of 600 people regarding COVID-19 vaccines in South Africa, which revealed that 21% of South Africans were strongly unwilling to be vaccinated..."

The researchers conclude that, despite acknowledged limitations, "Ultimately, building on insights from this study, public health and media actors can be stimulated to develop or re-evaluate relevant policies that promote responsible media use and public consumption to maximize the benefits of health interventions amid the COVID-19 crisis. This does not undermine the efficacy of efforts already made to curb misleading information regarding COVID-19 in the public space."