Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    sales and data analytics
    How Data Analytics Improves Lead Management and Sales Results
    9 Min Read
    data analytics and truck accident claims
    How Data Analytics Reduces Truck Accidents and Speeds Up Claims
    7 Min Read
    predictive analytics for interior designers
    Interior Designers Boost Profits with Predictive Analytics
    8 Min Read
    image fx (67)
    Improving LinkedIn Ad Strategies with Data Analytics
    9 Min Read
    big data and remote work
    Data Helps Speech-Language Pathologists Deliver Better Results
    6 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Visualizing Reuters Editorial Investment
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Big Data > Data Visualization > Visualizing Reuters Editorial Investment
Data Visualization

Visualizing Reuters Editorial Investment

matthewhurst
matthewhurst
1 Min Read
SHARE

This is a very early view of a work in progress. The process is to crawl Reuters, extract the attribution of each article (writers and editors) and extract the mention of country names. Then, using gephi, to visualize the relationships, thus – in this case – showing which editors are associated with the mention of which countries. In this snippet, countries have mutual links (red) with other countries they are collocated with. Editors have directed edges (green) with the country mentions they are associated with.

This is a very early view of a work in progress. The process is to crawl Reuters, extract the attribution of each article (writers and editors) and extract the mention of country names. Then, using gephi, to visualize the relationships, thus – in this case – showing which editors are associated with the mention of which countries. In this snippet, countries have mutual links (red) with other countries they are collocated with. Editors have directed edges (green) with the country mentions they are associated with.

CountriesEditors

 

 

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

sales and data analytics
How Data Analytics Improves Lead Management and Sales Results
Analytics Big Data Exclusive
ai in marketing
How AI and Smart Platforms Improve Email Marketing
Artificial Intelligence Exclusive Marketing
AI Document Verification for Legal Firms: Importance & Top Tools
AI Document Verification for Legal Firms: Importance & Top Tools
Artificial Intelligence Exclusive
AI supply chain
AI Tools Are Strengthening Global Supply Chains
Artificial Intelligence Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

Big Data Is The Next Frontier For Innovation, Competition and Productivity

3 Min Read

2 Ways Big Data and Little Data Are the Perfect Couple

5 Min Read

On Text Analytics vs Machine Translation

4 Min Read

Wordtree for Visual Text Exploration

5 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

giveaway chatbots
How To Get An Award Winning Giveaway Bot
Big Data Chatbots Exclusive
ai is improving the safety of cars
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?