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The deadly threat caused by the rapid spread of COVID-19 has been restricted by virtue of vaccines. However, there is misinformation regarding the certainty and positives outcome of getting vaccinated; hence, many people are reluctant to opt for it. Therefore, in this paper, we identified public sentiments and hesitancy toward the COVID-19 vaccines based on Instagram posts as part of intelligent surveillance. We first retrieved more than 10k publicly available comments and captions posted under different vaccine hashtags (namely, covaxin, covishield, and sputnik). Next, we translated the extracted comments into a common language (English), followed by the calculation of the polarity score of each comment, which helped identify the vaccine sentiments and opinions in the comments (positive, negative, and neutral) with an accuracy of more than 80%. Moreover, upon analysing the sentiments, we found that covaxin received 71.4% positive, 18.5% neutral, and 10.1% negative comments; covishield obtained 64.2% positive, 24.5% neutral, and 11.3% negative post; and sputnik received 55.8% positive, 15.5% neutral, and 28.7% negative sentiments. Understanding vaccination perceptions and views through Instagram comments, captions, and posts is helpful for public health officials seeking to enhance vaccine uptake by promoting positive marketing and reducing negative marketing. In addition to this, some interesting future directions are also suggested considering the investigated problem.
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Stored only when both papers are in the corpus — 13 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.