Data on social media contain a wealth of user information. Big data research of social media
data may also support standard surveillance approaches and provide decision-makers with …

Events are occurrences in specific locations, time, and semantics that nontrivially impact
either our society or the nature, such as earthquakes, civil unrest, system failures …

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 …

This study aims to forecast international tourist arrivals to Hong Kong from seven English-
speaking countries. A new direction in tourism demand modeling and forecasting is …

Based on internet big data from multiple sources (ie, the Baidu search engine and two
online review platforms, Ctrip and Qunar), this study forecasts tourist arrivals to Mount …

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 …

Prior to the innovation of information communication technologies (ICT), social interactions
evolved within small cultural boundaries such as geo spatial locations. The recent …

Generic sentiment calculations cannot fully reflect tourists' preferences, whereas fine-
grained sentiment analysis identifies tourists' precise attitudes. This study forecasted visitor …

Abstract Social Media Prediction (SMP) is an emerging powerful tool attracting the attention
of researchers and practitioners alike. Despite its many merits, SMP has also several …