Dense Vector Embedding Based Approach to Identify Prominent Disseminators From Twitter Data Amid COVID-19 Outbreak

Agarwal, Amit; Uniyal, Deepak; Toshniwal, Durga; Deb, Dipanjan

doi:10.1109/tetci.2021.3067661

Cited by 8 publications

(2 citation statements)

References 64 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Degree-Based Analysis [23,11,1,19,58] First, it calculates the degree of each node in the criminal network by counting their connections or associations. Nodes with higher degrees of connectivity are considered influential as they have more connections, allowing them to control information flow and criminal activities.…”

Section: Comparative Evaluationsmentioning

confidence: 99%

Techniques to Detect Crime Leaders within a Criminal Network: A Survey, Experimental, and Comparative Evaluations

Taha,

Shoufan

2024

Preprint

View full text Add to dashboard Cite

show abstract

Section: Comparative Evaluationsmentioning

confidence: 99%

Techniques to Detect Crime Leaders within a Criminal Network: A Survey, Experimental, and Comparative Evaluations

Taha,

Shoufan

2024

Preprint

View full text Add to dashboard Cite

show abstract

“…We subsequently identified more than 13 million tweets in twelve Indian Regional Languages (IRL) from the dataset collected. This dataset can be advantageous for researchers, Government authorities, and policymakers in studying the pandemic from a varied perspective as listed below [9][10] [11][12] [13][14]:…”

Section: Introductionmentioning

confidence: 99%

IRLCov19: A Large COVID-19 Multilingual Twitter Dataset of Indian Regional Languages

Uniyal¹,

Agarwal²

2021

Preprint

Self Cite

View full text Add to dashboard Cite

Emerged in Wuhan city of China in December 2019, COVID-19 continues to spread rapidly across the world despite authorities having made available a number of vaccines. While the coronavirus has been around for a significant period of time, people and authorities still feel the need for awareness due to the mutating nature of the virus and therefore varying symptoms and prevention strategies. People and authorities resort to social media platforms the most to share awareness information and voice out their opinions due to their massive outreach in spreading the word in practically no time. People use a number of languages to communicate over social media platforms based on their familiarity, language outreach, and availability on social media platforms. The entire world has been hit by the coronavirus and India is the second worst-hit country in terms of the number of active coronavirus cases. India, being a multilingual country, offers a great opportunity to study the outreach of various languages that have been actively used across social media platforms. In this study, we aim to study the dataset related to COVID-19 collected in the period between February 2020 to July 2020 specifically for regional languages in India. This could be helpful for the Government of India, various state governments, NGOs, researchers, and policymakers in studying different issues related to the pandemic. We found that English has been the mode of communication in over 64% of tweets while as many as twelve regional languages in India account for approximately 4.77% of tweets.

show abstract

IRLCov19: A Large COVID-19 Multilingual Twitter Dataset of Indian Regional Languages

Uniyal

Agarwal

2021

Communications in Computer and Information Science

View full text Add to dashboard Cite

Dense Vector Embedding Based Approach to Identify Prominent Disseminators From Twitter Data Amid COVID-19 Outbreak

Cited by 8 publications

References 64 publications

Techniques to Detect Crime Leaders within a Criminal Network: A Survey, Experimental, and Comparative Evaluations

Techniques to Detect Crime Leaders within a Criminal Network: A Survey, Experimental, and Comparative Evaluations

IRLCov19: A Large COVID-19 Multilingual Twitter Dataset of Indian Regional Languages

IRLCov19: A Large COVID-19 Multilingual Twitter Dataset of Indian Regional Languages

Contact Info

Product

Resources

About