| dc.contributor | 資科系 | |
| dc.creator (作者) | 劉吉軒 | |
| dc.creator (作者) | Liu, Jyi-shane | |
| dc.creator (作者) | Liu, Kwei-Guu | |
| dc.date (日期) | 2019-06 | |
| dc.date.accessioned | 22-Apr-2020 15:39:04 (UTC+8) | - |
| dc.date.available | 22-Apr-2020 15:39:04 (UTC+8) | - |
| dc.date.issued (上傳時間) | 22-Apr-2020 15:39:04 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/129360 | - |
| dc.description.abstract (摘要) | Outbreaks of social events can be viewed from two angles: anomalous changes of information or popular actions. Event detection algorithms focus on the former one, while the later one is measured by social event intensity, which is a rate to show how popular an action is in a social network at a given time. The rate is relatively intuitive and can give a holistic view about activity levels in a network, but its estimation isn`t easy. Inspired by event detection algorithms, this study proposes an alternative measure, social event magnitude, by using the product of background influence and cooperation value. Background influence is extracted via non-backtracking matrices, and cooperation value is obtained via engagement capacities. This alternative measure does not just integrate multisource information, but also gives a holistic view about activity levels in a network. Social event magnitudes follow a long-tailed distribution; they can be visualized for changing activities and can be applied to online event detections. | |
| dc.format.extent | 110 bytes | - |
| dc.format.mimetype | text/html | - |
| dc.relation (關聯) | Proceedings of the Ninth ACM International Conference on Web Intelligence, Mining, and Semantics, Chung-Ang University, pp.Article No. 11 | |
| dc.title (題名) | Social Event Magnitudes via Background Influences and Engagement Capacities and its Applications | |
| dc.type (資料類型) | conference | |
| dc.identifier.doi (DOI) | 10.1145/3326467.3326481 | |
| dc.doi.uri (DOI) | https://doi.org/10.1145/3326467.3326481 | |
