PlumX Metrics
Embed PlumX Metrics

Rumour Veracity Estimation with Deep Learning for Twitter

IFIP Advances in Information and Communication Technology, ISSN: 1868-422X, Vol: 558, Page: 351-363
2019
  • 11
    Citations
  • 0
    Usage
  • 15
    Captures
  • 0
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    11
    • Citation Indexes
      11
  • Captures
    15

Conference Paper Description

Twitter has become a fertile ground for rumours as information can propagate to too many people in very short time. Rumours can create panic in public and hence timely detection and blocking of rumour information is urgently required. We proposed and compare machine learning classifiers with a deep learning model using Recurrent Neural Networks for classification of tweets into rumour and non-rumour classes. A total thirteen features based on tweet text and user characteristics were given as input to machine learning classifiers. Deep learning model was trained and tested with textual features and five user characteristic features. The findings indicate that our models perform much better than machine learning based models.

Provide Feedback

Have ideas for a new metric? Would you like to see something else here?Let us know