Event Cube for Suicidal Event Analysis: A Case Study

Qing Li, Zhihan Yan, Jun Li, Zhenguo yang, Zehang Lin, Hong Va Leong, Lei Chen, Nancy Xiaonan Yu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review


The publicly available data, such as the massive and dynamically updated news and social media data streams (a.k.a. big data), cover a wide range of social activities, personal views, and expressions. Effective research and application rely heavily on the ability of comprehending and discovering the knowledge patterns underlying this big data, from which the notion of an event
serves as a cornerstone in building up more complex knowledge structures. Establishing methodologies and techniques for discovering real-world events from such large amounts of data, as well as for managing and analyzing such events in an efficient and aesthetic manner, is crucial and challenging. In this paper, we
present an event cube framework devised to support various collection, consolidation, fusion, and analysis tasks for suicidal events. More specifically, we present a mechanism for data collection over multiple data sources in both passive and active manners, and promote the mappings constructed from various representation spaces for data consolidation. Furthermore, multimodal fusion is devised to integrate multiple data intrinsic structures and learn discriminative data representations so as to process heterogeneous multimodal data efficiently. Finally,
the event cube model is developed to support event organization and contextualization with hierarchical and analytical operations. A case study is provided to demonstrate the capabilities and benefits of our event cube facilities supporting on-line analytical processing of suicidal events and their relationships.
Original languageEnglish
Title of host publicationProceedings of International Conference on Web Information Systems Engineering
Number of pages15
ISBN (Print)978-3-030-90887-4
Publication statusPublished - Oct 2021


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