Anzeige
Erschienen in:
2017 | OriginalPaper | Buchkapitel
Classifying Tweets Using User Account Information
verfasst von : John Khoury, Charles Li, Chloe Lo, Corinne Lee, Shakeel Rajwani, David Woolfolk, Alexis-Walid Ahmed, Loredana Crusov, Arnold Pérez-Goicochea, Christopher Romero, Rob French, Vasco Ribeiro
Erschienen in: Augmented Cognition. Neurocognition and Machine Learning
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Abstract
Twitter is a short-text message system developed 6 years ago. It now has more than 100 million users generating over 300 million tweets every day. Twitter accounts are used for diverse purposes, such as social, advertising, political, religious, benevolent or vicious ideologies, among other activities. These activities can be communicated by humans, a machine or a robot. The purpose of this paper is to build predictive models, such as Logistic Regression, K Nearest Neighbors and Neural Network in order to identify the best variables that help predict, based on the contents, whether the tweets are coming from a human or a machine with the least possible error.