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.
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.
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.
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.
