TWSDetection
Machine Learning for Trend and Weak Signal Detection in Social Networks and Social Media

Table of Contents

• Preface
  
  

Session 1: Risk and Trend Detection

• Targeting Societal Challenges by analysing social media data (abstract) 1-2
  Miriam Fernandez
• What's in the News? Identification of Trending Topics in Alternative and Mainstream Lithuanian Media 3-17
  Justina Mandravickaitė, Monika Briedienė, Jonas Uus, Tomas Krilavičius
• Topical Community Detection: an Embedding User and Content Similarity Method (short paper) 18-24
  Thi Bich Ngoc Hoang
• Prediction and Visual Intelligence Platform for Detection of Irregularities and Abnormal Behaviour (short paper) 25-30
  Konstantinos Demestichas, Theodoros Alexakis, Nikolaos Peppes, Konstantina Re-moundou, Ioannis Loumiotis, Wilmuth Müller, Konstantinos Avgerinakis

Session 2: Detection of aggressive content

• Deep learning with weakly-annotated data: a sound event detection use case (and hate speech detection here and there) (abstract) 31-32
  Thomas Pellegrini
• The Role of Storylines in Hate Speech Detection (short paper) 33-39
  Kurt Englmeier
• Aggression Identification in Posts - two machine learning approache 40-49
  Faneva Ramiandrisoa
• Hatemeter Project: Analysis of hate speech on twitter at the crossroads of computer science, humanities and social sciences (short paper) 50-55
  Mario Laurent

Session 3: Fake news detection

• An ML Model for Predicting Information Check-Worthiness using a Variety of Features (short paper) 56-61
  Md Zia Ullah
• Detecting fake news in social media content (abstract) 62-63
  Charles Huot, Sonia Collada

Session 4: Another Session

• Ethical and legal challenges of machine learning for trend and weak signal detection in social networks: an overview (abstract) 64-65
  Zuzanna Warso
• Intelligence analysis and semantic interoperability for identity resolution (abstract) 66-67
  Kostas Davarakis, Eva Blomqvist