Defining, Detecting, and Characterizing Power Users in Threads DOI Creative Commons
Gianluca Bonifazi,

Christopher Buratti,

Enrico Corradini

и другие.

Big Data and Cognitive Computing, Год журнала: 2025, Номер 9(3), С. 69 - 69

Опубликована: Март 16, 2025

Threads is a new social network that was launched by Meta in July 2023 and conceived as direct alternative to X. It unique case study the landscape, it content-based like X, but has an Instagram-based growth model, which makes significantly different from As recently, studies on are still scarce. One of most common investigations networks regards power users (also called influencers, lead users, influential etc.), i.e., those who can influence information dissemination, user behavior, ultimately current dynamics future development network. In this paper, we want contribute knowledge showing there indeed then attempt understand main features characterize them. The definition adopt here novel leverages four classical centrality measures Social Network Analysis. This ensures our benefit enormous accumulated literature over years. order conduct analysis, had build dataset, none existed contained necessary for studies. Once built such decided make open thus available all researchers perform analyses Threads. characterization contributions paper.

Язык: Английский

Defining, Detecting, and Characterizing Power Users in Threads DOI Creative Commons
Gianluca Bonifazi,

Christopher Buratti,

Enrico Corradini

и другие.

Big Data and Cognitive Computing, Год журнала: 2025, Номер 9(3), С. 69 - 69

Опубликована: Март 16, 2025

Threads is a new social network that was launched by Meta in July 2023 and conceived as direct alternative to X. It unique case study the landscape, it content-based like X, but has an Instagram-based growth model, which makes significantly different from As recently, studies on are still scarce. One of most common investigations networks regards power users (also called influencers, lead users, influential etc.), i.e., those who can influence information dissemination, user behavior, ultimately current dynamics future development network. In this paper, we want contribute knowledge showing there indeed then attempt understand main features characterize them. The definition adopt here novel leverages four classical centrality measures Social Network Analysis. This ensures our benefit enormous accumulated literature over years. order conduct analysis, had build dataset, none existed contained necessary for studies. Once built such decided make open thus available all researchers perform analyses Threads. characterization contributions paper.

Язык: Английский

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