About: A Toolkit for Analyzing and Visualizing Online Users via Reshare Cascade Modeling

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	A Toolkit for Analyzing and Visualizing Online Users via Reshare Cascade Modeling
Creator	Kong, Quyu Ram, Rohit Rizoiu, Marian-Andrei
Source	ArXiv
abstract	Modeling online discourse dynamics is a core activity in understanding the spread of information, both offline and online, and emergent online behavior. There is currently a disconnect between the practitioners of online social media analysis - usually social, political and communication scientists - and the accessibility to tools capable of handling large quantities of online data, and examining online users and their behavior. We present two tools,birdspotter and evently, for analyzing online users based on their involvement in retweet cascades. birdspotter provides a toolkit to measure social influence and botnets of Twitter users. While it leverages the multimodal information of tweets, such as text contents, evently augments the user measurement by modeling the temporal dynamics of information diffusions using self-exciting processes. Both tools are designed for users with a wide range of computer expertise and include tutorials and detailed documentation. We illustrate a case study of a topical dataset relating to COVID-19, using both tools for end-to-end analysis of online user behavior.
has issue date	2020-06-11(xsd:dateTime)
has license	arxiv
sha1sum (hex)	2b40a59106b9b5cbfb848d2e7d8c99ed6f2ad9f8
resource representing a document's title	A Toolkit for Analyzing and Visualizing Online Users via Reshare Cascade Modeling
resource representing a document's body	covid:2b40a59106b9b5cbfb848d2e7d8c99ed6f2ad9f8#body_text
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