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Information retrieval of a disaster event from cross-platform social media
- Source :
- Information Discovery and Delivery. 45:220-226
- Publication Year :
- 2017
- Publisher :
- Emerald, 2017.
-
Abstract
- Purpose The purpose of this study is to propose a method to retrieve data on an event based on a preliminary collection of event-specific hashtags. Design/methodology/approach Extra knowledge, or a list of events with recorded features that can be used to characterize an event and separate it from other simultaneously occurring social phenomena, is employed. The first step involves the estimation and use of the impact area to retrieve messages from Twitter. This is followed by an extraction of hashtags from these messages. After that, the noisy hashtags would be filtered out by some heuristic rules. Finally, hashtags are used to collect relevant messages from not only Twitter but also other social media platforms. Findings The proposed method has high selectivity and is able to collect distinct sets of hashtags even for similar simultaneous events. In addition, spatial and temporal features are sufficient to improve collecting information of disaster events. Originality/value This work discusses a method of information retrieval of an event from cross-platform social media. The proposed method can be applied to other studies of geographically related events.
- Subjects :
- Information retrieval
General Computer Science
Computer science
Event (computing)
Heuristic
media_common.quotation_subject
High selectivity
0211 other engineering and technologies
02 engineering and technology
Library and Information Sciences
computer.software_genre
01 natural sciences
Support vector machine
010104 statistics & probability
Originality
Cross-platform
Social media
Data mining
0101 mathematics
computer
Impact area
021101 geological & geomatics engineering
media_common
Subjects
Details
- ISSN :
- 23986247
- Volume :
- 45
- Database :
- OpenAIRE
- Journal :
- Information Discovery and Delivery
- Accession number :
- edsair.doi...........f0cb5f577711bfd922bb0a614bd234a3
- Full Text :
- https://doi.org/10.1108/idd-01-2017-0003