Please use this identifier to cite or link to this item:
Title: Stream text data analysis on twitter using apache spark streaming
Authors: Hakdağlı, Özlem
Özcan, Caner
Oğul, İskender Ülgen
Keywords: Apache Spark
Spark Streaming
Machine Learning
Text Mining
Issue Date: 2018
Publisher: Institute of Electrical and Electronics Engineers Inc.
Series/Report no.: Signal Processing and Communications Applications Conference
Abstract: With today's developing technology, people's access to information and its production have reached a very fast level. These generated and obtained information are instantly created, entered into data systems and updated. Sources of streaming data can be transformed into valuable analysis results when they are handled with targeted methods. In this study, a text data field is determined to perform analysis on instantaneous generated data and Twitter, the richest platform for instant text data, is used. Twitter instantly generates a variety of data in large quantities and it presents it as open source using an API. A machine learning framework Apache Spark's stream analysis environment is used to analyze these resources. Situation analysis was performed using Support Vector Machine, Decision Trees and Logistic Regression algorithms presented under this environment. The results are presented in tables.
Description: 26th IEEE Signal Processing and Communications Applications Conference (SIU)
ISBN: 978-1-5386-1501-0
ISSN: 2165-0608
Appears in Collections:WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Show full item record

CORE Recommender


checked on Mar 18, 2023

Page view(s)

checked on Mar 20, 2023

Google ScholarTM



Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.