Sentiment, Count and Cases: Analysis of Twitter discussions during COVID-19 Pandemic

Research article (2020 7th International Conference on Behavioural and Social Computing (BESC), 2020) · cited 16× · AI/ML

academia openalex:W3133275718

Press Enter · cited answer in seconds

Sentiment, Count and Cases: Analysis of Twitter discussions during COVID-19 Pandemic

Summary

Sentiment, Count and Cases: Analysis of Twitter discussions during COVID-19 Pandemic is a scholarly article^[1].

Key Facts

Sentiment, Count and Cases: Analysis of Twitter discussions during COVID-19 Pandemic's instance of is recorded as scholarly article^[2].

⭐ Popularity Graph

0/100 long tail

Quick Facts

Instance of scholarly article

🔗 Connections

Authored by 2

Sardar Haider Waseem Ilyas, Zainab Tariq Soomro

← Author of 2

Sardar Haider Waseem Ilyas, Zainab Tariq Soomro

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

[2] ↑ Sentiment, Count and Cases: Analysis of Twitter discussions during COVID-19 Pandemic — instance of (P31): scholarly article. wikidata.org.

Class ancestry

[1] ↑ Sentiment, Count and Cases: Analysis of Twitter discussions during COVID-19 Pandemic is an instance of scholarly article (scholarly article) [P31, primary]. Wikidata. wikidata.org.

📑 Cite this page

Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA

4ort.xyz Knowledge Graph. (2026). Sentiment, Count and Cases: Analysis of Twitter discussions during COVID-19 Pandemic. Retrieved May 24, 2026, from https://4ort.xyz/entity/sentiment-count-and-cases-analysis-of-twitter-discussions-during-covid-19-pandemic

MLA

“Sentiment, Count and Cases: Analysis of Twitter discussions during COVID-19 Pandemic.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/sentiment-count-and-cases-analysis-of-twitter-discussions-during-covid-19-pandemic.

BibTeX

@misc{4ortxyz_sentiment-count-and-cases-analysis-of-twitter-discussions-during-covid-19-pandemic_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Sentiment, Count and Cases: Analysis of Twitter discussions during COVID-19 Pandemic}}, year = {2026}, url = {https://4ort.xyz/entity/sentiment-count-and-cases-analysis-of-twitter-discussions-during-covid-19-pandemic}, note = {Accessed: 2026-05-24}}

LLM prompt

According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Sentiment, Count and Cases: Analysis of Twitter discussions during COVID-19 Pandemic — https://4ort.xyz/entity/sentiment-count-and-cases-analysis-of-twitter-discussions-during-covid-19-pandemic (retrieved 2026-05-24)

Canonical URL: https://4ort.xyz/entity/sentiment-count-and-cases-analysis-of-twitter-discussions-during-covid-19-pandemic · Last refreshed: May 24, 2026