Cultural and Geolocation Aspects of Communication in Twitter: The 3rd ASE International Conference on Social Informatics

Elena Daehnhardt, Nicholas Taylor, Yanguo Jing

Research output: Other contributionpeer-review

Abstract

Web applications exploit user information from social networks and online user activities to facilitate interaction and create an enhanced user experience. Due to privacy issues, however, it might be difficult to extract user data from social network, in particular location data. For instance, information on user location depends on users’ agreement to share own geographic data. Instead of directly collecting personal user information, we aim to infer user preferences by detecting behaviour patterns from publicly available microblogging content and users’ followers’ network. With statistical and machine-learning methods, we employ Twitter-specific features to predict country origin of users on Twitter with an accuracy of more than 90% for users from the most active countries. We further investigate users’ interpersonal communication with their followers. Our findings reveal that belonging to a particular cultural group is playing an important role in increasing users responses to their friends. The knowledge on user cultural origins thus could provide a differentiated state-of-the-art user experience in microblogs, for instance, in friend recommendation scenario.
Original languageEnglish
PublisherWorld Academy of Science, Engineering and Technology
ISBN (Print)978-1-62561-003-4
Publication statusPublished - 14 Dec 2014

Keywords

  • Learning systems
  • Positive Lons
  • Communication
  • preference behavior
  • social network
  • cation
  • Statistical learning
  • User Preferences
  • User experience
  • Web Application
  • privacy
  • Machine learning
  • Predict
  • scenario

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