This paper's top-level goal is to provide an overview of research conducted in the many
academic domains concerned with forecasting. By providing a summary encompassing …

Knowledge Graph (KG) reasoning that predicts missing facts for incomplete KGs has been
widely explored. However, reasoning over Temporal KG (TKG) that predicts facts in the …

Knowledge graph reasoning is a critical task in natural language processing. The task
becomes more challenging on temporal knowledge graphs, where each fact is associated …

Temporal Knowledge Graphs (TKGs) have been developed and used in many different
areas. Reasoning on TKGs that predicts potential facts (events) in the future brings great …

Over the last decade, event prediction has drawn attention from both academic and industry
communities, resulting in a substantial volume of scientific papers published in a wide range …

Proactive handling of social unrest events which are common happenings in both
democracies and authoritarian regimes requires that the risk of upcoming social unrest …

The need for new methods to deal with big data is a common theme in most scientific fields,
although its definition tends to vary with the context. Statistical ideas are an essential part of …

Temporal knowledge graphs (TKGs) extrapolation reasoning predicts future events based
on historical information, which has great research significance and broad application value …

Geotagging Twitter messages is an important tool for event detection and enrichment.
Despite the availability of both social media content and user network information, these two …

Social media has both been hailed for enabling social movements and critiqued for its
affordances as a surveillance infrastructure. In this work, I focus on the latter by analyzing …