DESPIC: Detecting Early Signatures of Persuasion in Information Cascades

The goal of DESPIC project was developing a technological infrastructure to automatically detect orchestrated campaigns on social media in their early stage of diffusion. Such campaigns include rumors, spread of misinformation, persuasion attempts, and advertising. We designed and implemented a dist...

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Bibliographic Details
Main Authors: Flammini, Alessandro, Menczer, Filippo, Mei, Qiaozhu, Malinchik, Sergey
Format: Report
Language:English
Subjects:
ARCHIVES
CASCADE STRUCTURES
CLUSTERING
COLLECTION
DETECTION
DISTRIBUTION
EFFICIENCY
IDENTIFICATION
INFORMATION RETRIEVAL
INFRASTRUCTURE
INTERNET
LEARNING
Miscellaneous Detection and Detectors
PREDICTIONS
SCENARIOS
SIGNATURES
SOCIAL COMMUNICATION
SOCIAL MEDIA
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Summary:The goal of DESPIC project was developing a technological infrastructure to automatically detect orchestrated campaigns on social media in their early stage of diffusion. Such campaigns include rumors, spread of misinformation, persuasion attempts, and advertising. We designed and implemented a distributed infrastructure for the efficient collection, archival and retrieval of Twitter data, and a framework for clustering messages in topically coherent memes in a streaming scenario. Our infrastructure has served as the basis for the development of machine learning infrastructures to discriminate between naturally trending and promoted content, the identification of social bots, the identification of rumors, and the prediction of burstiness and popularity of memes. The original document contains color images.