Nattiya Kanhabua
Sara Romano
ABSTRACT
Microblogging services, such as Twitter, are gaining interests as a means of sharing information in social networks. Numerous works have shown the potential of using Twitter posts (or tweets) in order to infer the existence and magnitude of real-world events. In the medical domain, there has been a surge in detecting public health related tweets for early warning so that a rapid response from health authorities can take place. In this paper, we present a temporal analytics tool for supporting a comparative, temporal analysis of disease outbreaks between Twitter and official sources, such as, World Health Organization (WHO) and ProMED-mail. We automatically extract and aggregate outbreak events from official outbreak reports, producing time series data. Our tool can support a correlation analysis and an understanding of the temporal developments of outbreak mentions in Twitter, based on comparisons with official sources.
- E. Aramaki, S. Maskawa, and M. Morita. Twitter catches the flu: Detecting influenza epidemics using twitter. In Proceedings of EMNLP '2011, 2011. Google Scholar
Digital Library
- M. Cataldi, L. Di Caro, and C. Schifanella. Emerging topic detection on twitter based on temporal and social terms evaluation. In Proceedings of MDMKDD '2010, 2010. Google ScholarDigital Library
- A. Culotta. Towards detecting influenza epidemics by analyzing twitter messages. In Proceedings of the First Workshop on Social Media Analytics (SOMA '2010), 2010. Google ScholarDigital Library
- V. Lampos and N. Cristianini. Nowcasting events from the social web with statistical learning. ACM TIST, 3, 2011. Google ScholarDigital Library
- M. J. Paul and M. Dredze. You are what you tweet: Analyzing twitter for public health. In Proceedings of ICWSM '2011, 2011.Google Scholar
- T. Sakaki, M. Okazaki, and Y. Matsuo. Earthquake shakes twitter users: real-time event detection by social sensors. In Proceedings of WWW '2010, 2010. Google ScholarDigital Library
- J. Strötgen and M. Gertz. Heideltime: High quality rule-based extraction and normalization of temporal expressions. In Proceedings of the 5th International Workshop on Semantic Evaluation, 2010. Google ScholarDigital Library
Index Terms
- Supporting temporal analytics for health-related events in microblogs
Recommendations
Observatory of trends in software related microblogs
ASE '12: Proceedings of the 27th IEEE/ACM International Conference on Automated Software EngineeringMicroblogging has recently become a popular means to disseminate information among millions of people. Interestingly, software developers also use microblog to communicate with one another. Different from traditional media, microblog users tend to ...
News comments generation via mining microblogs
WWW '12 Companion: Proceedings of the 21st International Conference on World Wide WebMicroblogging websites such as Twitter and Chinese Sina Weibo contain large amounts of microblogs posted by users. Many of these microblogs are highly sensitive to the important real-world events and correlated to the news events. Thus, microblogs from ...
Characterizing communal microblogs during disaster events
ASONAM '16: Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and MiningMillions of microblogs are posted during disasters, which include not only information about the present situation, but also the emotions / opinions of the masses. While most of the prior research has been on extracting situational information, this ...
Comments