Name
Abstract | ||
|---|---|---|
There are many disasters such as big earthquakes, flood disasters, hurricanes, and typhoons. Especially in Japan, there are so many natural disasters. Nowadays, after the disaster, we help each other not only in the real world but also on the social media. However, there are many rumors on the social media. Especially, twitter spreads many rumors after the disaster, because it is easy to spread information. According to our former study, there are many behavioral facilitation tweets in the rumors tweets. We consider it is important to extract automatically such rumor behavioral facilitation tweets. In this paper, as a first step of extracting rumor behavioral facilitation tweets, we propose the method which extracts behavioral facilitation tweets from disaster tweets. Our proposed method is rule-based. We also conducted the small experiment to measure our proposed method is suitable for extracting behavioral facilitation tweets.
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Year | DOI | Venue |
|---|---|---|
2018 | 10.1145/3282373.3282852 | iiWAS |
Keywords | Field | DocType |
Disaster situation, Twitter, behavioral facilitation tweet, rumor | Data science,Data mining,Social media,Facilitation,Computer science,Rumor,Natural disaster,Flood myth | Conference |
Citations | PageRank | References |
0 | 0.34 | 11 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Keiichi Mizuka | 1 | 2 | 1.07 |
| Yu Suzuki | 2 | 4 | 4.21 |
| Akiyo Nadamoto | 3 | 189 | 34.24 |