This study focuses on the Twitter suspension mechanism and the analysis of shared content and features of the user accounts that may lead to this.
We collect the ground truth for our dataset through the Twitter API suspended accounts collection, containing approximately 343K of bot accounts and 8M of normal users.
Modern Internet of Things (IoT) environments are monitored via a large number of IoT enabled sensing devices, with the data acquisition and processing infrastructure setting restrictions in terms of computational power and energy resources.
Twitter is one of the most popular social networks attracting millions of users, while a considerable proportion of online discourse is captured.
A feedforward/backpropagate process optimizes these weights to match ideal propagation outcomes (normalized network power outputs) to wireless user emissions (normalized network power inputs).
A network of SDMs deployed over objects within an area, such as a floorplan walls, creates programmable wireless environments (PWEs) with fully customizable propagation of waves within them.
We further explore the mismatch between user actions and information exposure and find that older versions of the official Twitter apps follow a privacy-invasive policy of including precise GPS coordinates in the metadata of tweets that users have geotagged at a coarse-grained level (e. g., city).
Computers and Society Cryptography and Security