ArticleChaos, solitons, and fractals2020
Identification of influential users on Twitter: A novel weighted correlated influence measure for Covid-19.
Article in Chaos, solitons, and fractals, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Content hubs, information flows, and reactions for pesticide-related discussions on Twitter/X.Integrated environmental assessment and management · 2025Article
- Cryptocurrency Turmoil: Unraveling the Collapse of a Unified Stablecoin (USTC) through Twitter as a Passive Sensor.Sensors (Basel, Switzerland) · 2024Article
- Deciphering Influence on Social Media: A Comparative Analysis of Influential Account Detection Metrics in the Context of Tobacco Promotion.Social media + society · 2024Article
- Investigating the aftermath of the Türkiye 2023 earthquake: exploring post-disaster uncertainty among Syrian migrants using social network analysis with public health approach.Frontiers in public health · 2023Article
- Detecting COVID-19 vaccine hesitancy in India: a multimodal transformer based approach.Journal of intelligent information systems · 2023Article
- Recognition of opinion leaders in blockchain-based social networks by structural information and content contribution.PeerJ. Computer science · 2023Article
- A Survey on Social Media Influence Environment and Influencers Identification.Social network analysis and mining · 2022Review
- The Influence of Entrepreneurs' Online Popularity and Interaction Behaviors on Individual Investors' Psychological Perception: Evidence From the Peer-To-Peer Lending Market.Frontiers in psychology · 2022Article
- Spain's Hesitation at the Gates of a COVID-19 Vaccine.Vaccines · 2021Article
- Four-tier response system and spatial propagation of COVID-19 in China by a network model.Mathematical biosciences · 2020Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the era of advanced mobile technology, freedom of expression over social media has become prevalent among online users. This generates a huge amount of communication that eventually forms a ground for extensive research and analysis. The social network analysis allows identifying the influential people in society over microblogging platforms. Twitter, being an evolving social media platform, has become increasingly vital for online dialogues, trends, and content virality. Applications of discovering influential users over Twitter are manifold. It includes viral marketing, brand analysis, news dissemination, health awareness spreading, propagating political movement, and opinion leaders for empowering governance. In our research, we have proposed a sustainable approach, namely Weighted Correlated Influence (WCI), which incorporates the relative impact of timeline-based and trend-specific features of online users. Our methodology considers merging the profile activity and underlying network topology to designate online users with an influence score, which represents the combined effect. To quantify the performance of our proposed method, the Twitter trend #CoronavirusPandemic is used. Also, the results are validated for another social media trend. The experimental outcomes depict enhanced performance of proposed WCI over existing methods that are based on precision, recall, and F1-measure for validation.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.