Twitter_AnalysisForCrisis

[hiroshinagaya]

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[hiroshinagaya]

Fukushima

[Title] \bibitem{Tsubokura18}Tsubokura, Masaharu, et al. "Twitter use in scientific communication revealed by visualization of information spreading by influencers within half a year after the Fukushima Daiichi nuclear power plant accident." PloS one 13.9 (2018).

[Abstract]

[memo] According to Tsubokura et al.\cite{Tsubokura18}, the majority of retweets on the Fukushima disaster were based on original posts sent out by a few hundred accounts held by people described as influencers. Influencers play an important role in information propagation on social media. In the context of the dataset of interest in this study, the influencers communicated important information relating to the emergency efficiently.

[hiroshinagaya]

\bibitem{Takahashi15} Takahashi, Bruno, Edson C. Tandoc Jr, and Christine Carmichael. "Communicating on Twitter during a disaster: An analysis of tweets during Typhoon Haiyan in the Philippines." Computers in Human Behavior 50 (2015): 392-398.

Highlights •A typology of Twitter use before, during, and after Typhoon Haiyan was tested. •Time of use, location, type of user, and social media engagement were tested. •Retweet information, coordinate relief, and memorialize victims were the main uses. •Recommendations for future research and applications in crises are presented.

[hiroshinagaya]

\bibitem{Getchell16} Getchell, Morgan C., and Timothy L. Sellnow. "A network analysis of official Twitter accounts during the West Virginia water crisis." Computers in Human Behavior 54 (2016): 597-606.

Highlights •We analyzed a Twitter network of 41 accounts related to the W.V. water crisis. •We examined the network in the context of rapid dissemination of info in a crisis. •The networks density is lower than ideal from a crisis communication perspective. •There are 2 factions: national level organizations and W.V. organizations.

[hiroshinagaya]

\bibitem{Bunker17} Bunker, Deborah, Milad Mirbabaie, and Stefan Stieglitz. "Convergence behaviour of bystanders: an analysis of 2016 Munich shooting Twitter crisis communication." Proceedings of the Australasian Conference on Information Systems. 2017.

[hiroshinagaya]

\bibitem{Subba17}Subba, Rajib, and Tung Bui. "Online convergence behavior, social media communications and crisis response: An empirical study of the 2015 nepal earthquake police twitter project." Proceedings of the 50th hawaii international conference on system sciences. 2017.

[hiroshinagaya]

Fukushima

[Title] \bibitem{Rantasila18} Rantasila, Anna, et al. "#fukushima Five Years On: A Multimethod Analysis of Twitter on the Anniversary of the Nuclear Disaster." International Journal of Communication 12 (2018): 22.

[Abstract] This article examines how the fifth anniversary of the Fukushima Daiichi nuclear disaster was commemorated on English-speaking Twitter in March 2016. By combining social network analysis and critical discourse analysis, a research design is developed that can be applied to study the structure of actors and interpretative resources invoked in the crafting of communal remembrance of a disruptive, global media event. In the study, we explore the most visible actors and the most dominant meanings in the #fukushima stream. According to our analysis, the most significant players were the mainstream media and other established organizations. While most of the retweeted messages contained a ritual element of collective memory work, grief, and observance, another prominent feature was the strongly politicized discourse surrounding the aftermath of the disaster.

[Memo]

• 震災5周年の2016/3の1ヶ月間で、英語によってつぶやかれたTweetを分析（定点観測）
• There is a research which examines how the fifth anniversary of the Fukushima Daiichi nuclear disaster was commemorated on English-speaking Twitter in March 2016 \cite{Rantasila18}. They found that while most of the retweeted (influencing) messages contained a ritual element of collective memory work, grief, and observance, another prominent feature was the strongly politicized discourse surrounding the aftermath of the disaster.

[hiroshinagaya]

Fukushima

[Title] \bibitem{Aoki18} Aoki, Tomohiro, et al. "Analysis of the Regionality of the Number of Tweets Related to the 2011 Fukushima Nuclear Power Station Disaster: Content Analysis." JMIR public health and surveillance 4.4 (2018): e70.

Objective: The objective of the study was to assess differences in general practice presentations of allergic and infectious disease in those exposed to conurbation or urban living compared with rural environments.

Conclusions: Those living in conurbations or urban areas were more likely to consult a general practice for allergic rhinitis and upper respiratory tract infection. Both conurbation and rural living were associated with an increased risk of urinary tract infection. Living in rural areas was associated with an increased risk of asthma and lower respiratory tract infections. The data suggest that living environment may affect rates of consultations for certain conditions. Longitudinal analyses of these data would be useful in providing insights into important determinants.

[Memo]

• Twitterそのものの特徴に対する記述あり
• Rantasila et al. \cite{Rantasila18} examined how the fifth anniversary of the Fukushima Daiichi nuclear disaster was commemorated on English-speaking Twitter which include ``#fukushima'' in March 2016. They found that while most of the retweeted (influencing) messages contained a ritual element of collective memory work, grief, and observance, another prominent feature was the strongly politicized discourse surrounding the aftermath of the disaster.

[hiroshinagaya]

Fukushima

[Title] \bibitem{Li16} Li, Nan, et al. "Tweeting disaster: An analysis of online discourse about nuclear power in the wake of the Fukushima Daiichi nuclear accident." Journal of Science Communication 15.5 (2016): A02.

[Abstract] Of all the online information tools that the public relies on to collect information and share opinions about scientific and environmental issues, Twitter presents a unique venue to assess the spontaneous and genuine opinions of networked publics, including those about a focusing event like the Fukushima Daiichi nuclear accident following the 2011 Tohoku earthquake and tsunami. Using computational linguistic algorithms, this study analyzes a census of English-language tweets about nuclear power before, during, and after the Fukushima nuclear accident. Results show that although discourse about the event may have faded rapidly from the news cycle on traditional media, it evoked concerns about reactor safety and the environmental implications of nuclear power, particularly among users in U.S. states that are geographically closer to the accident site. Also, while the sentiment of the tweets was primarily pessimistic about nuclear power weeks after the accident, overall sentiment became increasingly neutral and uncertain over time. This study reveals there is a group of concerned citizens and stakeholders who are using online tools like Twitter to communicate about global and local environmental and health risks related to nuclear power. The implications for risk communication and public engagement strategies are discussed.

[memo]

[hiroshinagaya]

Fukushima

[Title] \bibitem{Su17} Su, Leona Yi-Fan, et al. "Analyzing public sentiments online: Combining human-and computer-based content analysis." Information, Communication & Society 20.3 (2017): 406-427.

[Abstract] Recent technological developments have created novel opportunities for analyzing and identifying patterns in large volumes of digital content. However, many content analysis tools require researchers to choose between the validity of human-based coding and the ability to analyze large volumes of content through computer-based techniques. This study argues for the use of supervised content analysis tools that capitalize on the strengths of human- and computer-based coding for assessing opinion expression. We begin by outlining the key methodological issues surrounding content analysis as performed by human coders and existing computational algorithms. After reviewing the most popular analytic approaches, we introduce an alternative, hybrid method that is aimed at improving reliability, validity, and efficiency when analyzing social media content. To demonstrate the usefulness of this method, we track nuclear energy- and nanotechnology-related opinion expression on Twitter surrounding the Fukushima Daiichi accident to examine the extent to which the volume and tone of tweets shift in directions consistent with the expected external influence of the event. Our analysis revealed substantial shifts in both the volume and tone of nuclear power-related tweets that were consistent with our expectations following the disaster event. Conversely, there was decidedly more stability in the volume and tone of tweets for our comparison issue. These analyses provide an empirical demonstration of how the presented hybrid method can analyze defined communication sentiment and topics from large-scale social media data sets. The implications for communication scholars are discussed.

[memo]

[hiroshinagaya]

Fukushima

[Title] \bibitem{Toriumi13}Toriumi, Fujio, et al. "Information sharing on Twitter during the 2011 catastrophic earthquake." Proceedings of the 22nd International Conference on World Wide Web. 2013.

[Abstract] Such large disasters as earthquakes and hurricanes are very unpredictable. During a disaster, we must collect information to save lives. However, in time disaster, it is difficult to collect information which is useful for ourselves from such traditional mass media as TV and newspapers that contain information for the general public. Social media attract attention for sharing information, especially Twitter, which is a hugely popular social medium that is now being used during disasters. In this paper, we focus on the information sharing behaviors on Twitter during disasters. We collected data before and during the Great East Japan Earthquake and arrived at the following conclusions:

Many users with little experience with such specific functions as reply and retweet did not continuously use them after the disaster. Retweets were well used to share information on Twitter. Retweets were used not only for sharing the information provided by general users but used for relaying the information from the mass media. We conclude that social media users changed their behavior to widely diffuse important information and decreased non-emergency tweets to avoid interrupting critical information.

[memo] Toriumi et al. \cite{Toriumi13} analyzed tweets that were posted before and after the accident to unravel how people share the information on Twitter during disasters. They deal with reply and retweet based on whether interaction occurred on the follower network. They concluded that social media users changed their behavior to widely diffuse important information and decreased non-emergency tweets to avoid interrupting critical information.

[hiroshinagaya]

Fukushima

[Title] \bibitem{Sakaki13}Sakaki, Takeshi, et al. "Regional analysis of user interactions on social media in times of disaster." Proceedings of the 22nd International Conference on World Wide Web. 2013.

[Abstract] Social media attract attention for sharing information, especially Twitter, which is now being used in times of disasters. In this paper, we perform regional analysis of user interactions on Twittter during the Great East Japan Earthquake and arrived at the following two conclusions:People diffused much more information after the earthquake, especially in the heavily-damaged areas; People communicated with nearby users but diffused information posted by distant users. We conclude that social media users changed their behavior to widely diffuse information.

[memo] Sakaki et al. also analyzed user interactions with regional information \cite{Sakaki13}. They concluded that people diffused much more information after the earthquake, especially in the heavily-damaged areas, and they communicated with nearby users but diffused information posted by distant users.

[hiroshinagaya]

Fukushima

[title] Doan, Son, Bao-Khanh Ho Vo, and Nigel Collier. "An analysis of Twitter messages in the 2011 Tohoku Earthquake." International conference on electronic healthcare. Springer, Berlin, Heidelberg, 2011.

[Abstract] . Social media such as Facebook and Twitter have proven to be a useful resource to understand public opinion towards real world events. In this paper, we investigate over 1.5 million Twitter messages (tweets) for the period 9th March 2011 to 31st May 2011 in order to track awareness and anxiety levels in the Tokyo metropolitan district to the 2011 Tohoku Earthquake and subsequent tsunami and nuclear emergencies. These three events were tracked using both English and Japanese tweets. Preliminary results indicated: 1) close correspondence between Twitter data and earthquake events, 2) strong correlation between English and Japanese tweets on the same events, 3) tweets in the native language play an important roles in early warning, 4) tweets showed how quickly Japanese people’s anxiety returned to normal levels after the earthquake event. Several distinctions between English and Japanese tweets on earthquake events are also discussed. The results suggest that Twitter data can be used as a useful resource for tracking the public mood of populations affected by natural disasters as well as an early warning system.

[Memo] 事故後1ヶ月後のツイートをテキストマイニングしてる

[hiroshinagaya]

Fukushima

[Title]

[Abstract]

[memo]

[hiroshinagaya]

Fukushima

\bibitem{Wilensky14} Wilensky, Hiroko. "Twitter as a navigator for stranded commuters during the great east Japan earthquake." ISCRAM. 2014.

\bibitem{Toriumi13} Toriumi, Fujio, et al. "Information sharing on Twitter during the 2011 catastrophic earthquake." Proceedings of the 22nd International Conference on World Wide Web. 2013.

\bibitem{Sakaki13} Sakaki, Takeshi, et al. "Regional analysis of user interactions on social media in times of disaster." Proceedings of the 22nd International Conference on World Wide Web. 2013.

\bibitem{Ng12} Ng, Kwan-Hoong, and Mei-Li Lean. "The Fukushima nuclear crisis reemphasizes the need for improved risk communication and better use of social media." Health physics 103.3 (2012): 307-310.

Social media, in particular Twitter, was actively used for both direct communication and for transmission and exchange of scientific information at the time of the earthquake

[hiroshinagaya]

[title] \bibitem{Dufty16} Dufty, Neil. "Twitter turns ten: its use to date in disaster management." Australian Journal of Emergency Management, The 31.2 (2016): 50.

[Abstract]

[memo] Twitter is a social media platform that allows users to distribute short messages (called ''tweets'') on the World Wide Web or through smartphone on apps \cite{Dufty16}.

[hiroshinagaya]

[title] \bibitem{Suh10} Suh, Bongwon, et al. "Want to be retweeted? large scale analytics on factors impacting retweet in twitter network." 2010 IEEE Second International Conference on Social Computing. IEEE, 2010.

[abstract] Retweeting is the key mechanism for information diffusion in Twitter. It emerged as a simple yet powerful way of disseminating information in the Twitter social network. Even though a lot of information is shared in Twitter, little is known yet about how and why certain information spreads more widely than others. In this paper, we examine a number of features that might affect retweetability of tweets. We gathered content and contextual features from 74M tweets and used this data set to identify factors that are significantly associated with retweet rate. We also built a predictive retweet model. We found that, amongst content features, URLs and hashtags have strong relationships with retweetability. Amongst contextual features, the number of followers and followees as well as the age of the account seem to affect retweetability, while, interestingly, the number of past tweets does not predict retweetability of a user’s tweet. We believe that this research would inform the design of sensemaking and analytics tools for social media streams.

[memo] Generally, we found that, amongst content features, URLs and hashtags correlate with retweetability. Amongst contextual features, the number of followers and followees as well as the age of the account seem to affect retweetability, while, interestingly, the number of past tweets does not predict retweetability of a user’s tweet. Overall, we hope that this research would inform the design of sensemaking and analytics tools for Twitter streams as well as other social information streams.

[hiroshinagaya]

Takayasu, Misako, et al. "Rumor diffusion and convergence during the 3.11 earthquake: a Twitter case study." PLoS one 10.4 (2015).

[hiroshinagaya]

Sakaki, T., Okazaki, M., & Matsuo, Y. (2010, April). Earthquake shakes Twitter users: real-time event detection by social sensors. In Proceedings of the 19th international conference on World wide web (pp. 851-860).

As described in this paper, we investigate the real-time interaction of events such as earthquakes in Twitter and propose an algorithm to monitor tweets and to detect a target event. -> Because of the numerous earthquakes and the large number of Twitter users throughout the country, we can detect an earthquake with high probability (96% of earthquakes of Japan Meteorological Agency (JMA) seismic intensity scale 3 or more are detected) merely by monitoring tweets.