University of Illinois Urbana-Champaign

Illinois Social Media Macroscope

Yun, Joseph T.; Chen, Wang; Troy, Joseph; Vance, Nickolas P.; Marini Luigi

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https://hdl.handle.net/2142/99742

Description

Title
Illinois Social Media Macroscope
Author(s)
  • Yun, Joseph T.
  • Chen, Wang
  • Troy, Joseph
  • Vance, Nickolas P.
  • Marini Luigi
Contributor(s)
  • Booth, Robert
  • Nelson, Todd
  • Hetrick, Ashley
  • Hodgkins, Hagen
Issue Date
2018-04-19
Keyword(s)
  • social media
  • data analytics
  • sentiment analysis
  • text classification
  • network analysis
  • text pre-processing
  • Twitter
  • Reddit
Abstract
In recent years, the explosion of social media platforms and the public collection of social data has brought forth a growing desire and need for research capabilities in the realm of social media and social data analytics. Research on this scale, however, requires a high level of computational and data-science expertise, limiting the researchers who are capable of undertaking social media data-driven research to those with significant computational expertise or those who have access to such experts as part of their research team. The Social Media Macroscope (SMM) is a science gateway with the goal of removing that limitation and making social media data, analytics, and visualization tools accessible to researchers and students of all levels of expertise. The SMM provides a single point of access to a suite of intuitive web interfaces for performing social media data collection, analysis, and visualization via for open-source and commercial tools. Within the SMM social scientists are able to process and store large datasets and collaborate with other researchers by sharing ideas, data, and methods. The first tool in the SMM is the Social Media Intelligence & Learning Environment (SMILE) which provides open source functions that collect social media data and analyze it. The tool currently provides access to Twitter and Reddit data and can perform text-preprocessing, sentiment analysis, network analysis and machine learned text classification. Future development of the SMM will add other social media collection and analysis tools and expand the capabilities of SMILE to include more functions and algorithms.
Type of Resource
  • text
  • other
Language
en
Permalink
http://hdl.handle.net/2142/99742
Copyright and License Information
2017 University of Illinois at Urbana Champaign, Technology Services, All rights reserved

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