About: 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.   Goto Sponge  NotDistinct  Permalink

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

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  • 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.
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  • Evaluation methods
  • Firefox OS software
  • Internet culture
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