A dataset of Ya'an Earthquake based on social media

减灾研究历史数据集专题 II 区论文（已发表） • 版本 EN3 Vol 3 (2) 2018.

Tian Chuanzhao, Li Guoqing, Yang Tengfei, Li Zhenyu

DOI: 10.11922/csdata.2018.0004.en
: 10.11922/sciencedb.560

： 2018 - 02 - 02

： 2018 - 03 - 14

： 2018 - 06 - 22

3476 11 0

Abstract & Keywords

Abstract: The Ya'an Earthquake occurred on April 20, 2013 (Beijing time). Its epicenter was located in Lushan County, Ya'an City, Sichuan Province, and the magnitude of this earthquake was 7.0. As of 14:30, April 24, the earthquake caused a total of 196 people dead, 21 missing and 11470 injured. With the development of information and communication technologies, microblog shows great potential in promoting emergency response as it provides an easily accessible platform on which disaster information could be assembled and rapidly disseminated to a large number of audiences. In view of this, we built the dataset of Ya'an Earthquake based on Sina-Weibo microblogs posted within Sichuan Province during 7 days after its occurrence. Sina-Weibo, a platform for information sharing and exchange, entertainment, leisure and life services, was launched in August 2009. It provides a platform where the public can communicate, express their feelings, offer suggestions, and so on – a platform that is essential for earthquake data search, query and publishing.

Keywords: Ya'an Earthquake; Sina-Weibo; Sichuan Province; data mining

Dataset Profile

Chinese Title	雅安地震灾情的社交媒体数据集
English Title	A dataset of Ya'an Earthquake based on social media
Data authors	Tian Chuanzhao, Li Guoqing, Yang Tengfei, Li Zhenyu
Corresponding data author	Li Guoqing
Time range	April 20 – 26, 2013
Geographical scope	Sichuan Province
Data volume	51418 records (about 5MB)
Data format	.xls
Data service system	<http://www.sciencedb.cn/dataSet/handle/560>
Source of funding	National Key Research and Development Program of China (2016YFE0122600) ; International Partnership Program of Chinese Academy of Sciences（131C11KYSB20160061）
Dataset composition	The data set consists of two parts of data: (1) "Data.rar" contains 21 tables of Sina-Weibo text data, and each table corresponds to a region; (2) "Classification sample.rar" is a sample subset illustrating the classification of the text data in "Data.rar".

1. Introduction

Ya'an Earthquake:¹ according to the China Earthquake Networks Center, the Ya'an Earthquake occurred at 8:02, April 20, 2013 (Beijing time). The epicenter was located in Lushan County, Ya'an City (30.3N, 103.0E), at a depth of 13 km, and the earthquake had a magnitude of 7.0. As of 10:00, April 24, 2013, 4045 aftershocks occurred, among which 103 were above magnitude 3, with the biggest being 5.7. An area of 12500 km² around the epicenter was affected, involving 1.52 million people. According to the China Earthquake Administration, the earthquake caused 196 people dead, 21 missing and 11470 injured as of 14:30, April 24. Figure 1 shows the location of earthquake occurrence.

Figure 1 Location of Ya'an Earthquake

Sina-Weibo,² an information sharing and exchange platform that provides entertainment, leisure, and other life services for the public, was launched in August 2009. By the end of March 2013, Sina-Weibo had a number of 536 million registered users, with an annual increase rate of 6.6%, and the number of its daily active users increased to 49.8 million, by 7.8% as of the end of 2012. Sina-Weibo provides timely updates about earthquake disasters. It is a platform where users are free to make searches and queries, where government bodies can post dynamic information about security and rescue, where the public can communicate to express their feelings, such as blessing, sadness, anger, anxiety, etc., and where users can propose to the government actions to be taken. Figure 2 shows some earthquake information at Sina-Weibo.

Figure 2 Earthquake information obtained from Sina-Weibo

There is growing evidence^8–11 that the public would look for disaster information most intensively during a certain period of time after its occurrence, irrespective of the sources.^3,6 As citizens can both access and post disaster information at open social platforms, such information constitutes a key part of effective responses to a major disaster.

On this aspect, research abroad goes earlier than the domestic. Glaser et al.⁴ analyzed Twitter data during the 2007 California Wildfires. Vieweg et al.⁵ researched on Twitter data for the 2009 Red River Floods and the 2009 Oklahoma Grassfires. It can be seen that Twitter has already been an effective channel for real-time updates. In China, scholars also studied the application of microblogs in formulating disaster response. Qu et al.⁶ analyzed people's responses to the 2008 Sichuan Earthquake based on Tianya Forum data, and Qu et at.⁷ analyzed people's responses to the 2010 Yushu Earthquake based on Sina-Weibo microblogs.

2. Data collection and processing

2.1 Overview

Using "Ya'an Earthquake" as the keywords, we searched Sina-Weibo text data posted within the geographical location of Sichuan Province during April 20 – 26, 2013. Each data record included: microblog content, time created, number of forwards, number of likes, number of comments and other information.

We first determined a city for data crawling and collected data from 21 cities of Sichuan Province. Due to Sina-Weibo's search limitations (i.e., up to 1000 records per search), we then determined a time interval for data crawling. Because of Sina-Weibo's search limitations, the amount of data would reach a peak during a certain period, or within 72 hours, after the earthquake occurrence, which is called the golden relief time. We collected Sina-Weibo data posted from all the cities of Sichuan Province during this period at a time interval of each hour. At other special time periods when Sina-Weibo data was released in particularly large quantities, we crawled data every few hours. However, at periods when the volume was small, we crawled data every few days. The data collected at respective time intervals was then stored into an appropriate data table.

We analyzed various counts of the 51418 earthquake-related messages collected within a week period after the earthquake occurrence. We counted the number of messages posted each day (indicated by the blue line in Figure 3), the number of messages forwarded (indicated by the red line in Figure 3), the number of messages commented (indicated by the green line in Figure 3) and the number of messages liked (indicated by the orange line in Figure 3).

Figure 3 Counts of Ya'an Earthquake-related messages

2.2 Data classification

We asked what types of messages people posted at Sina-Weibo in response to the earthquake. To answer the question, we randomly sampled 200 microblog messages for analysis. We identified six categories of content: emotion-related, opinion-related, action-related, situation updates, general information and others. Table 1 shows a summary of the categories.

Table 1 Classification of Sina-Weibo messages

Category	Description
Emotion-related	Expressing personal feelings such as blessing, sadness, anger, anxiety, etc.
Opinion-related	Criticizing or providing suggestions to the public, the government or rescue agencies.
Action-related	Requesting help, looking for missing people, or proposing relief actions or relief coordination.
Situation Updates	Updating factual information about the earthquake.
General Information	Any other earthquake relief-related information.
Others	Other earthquake-related information.

We applied the categories to sampled Sina-Weibo messages (Figure 4), and concluded 42% for emotion-related messages, 21% for action-related messages, 14% for situation updates, 8% for general information, 4% for opinion-related messages, and 11% for other messages on the earthquake.

Figure 4 Sample data classification

3. Sample description

The data retrieved from Sina-Weibo was stored into 21 tables. Each table corresponds to a city. Each data entry records information on the ID, content, location, time, forwardCount, commentCount, likeCount, keyword, province and city of the microblog posted.

Table 2 Sample data entry

Field Name	Description
ID	2231
Content	#Earthquake Live # 7.0 Ya'an Earthquake of Lushan: As of 18:00 April 21, there were 1642 aftershocks, including 78 aftershocks of magnitudes 3 and above, 4 of magnitude above 5.0 and above, and 18 of magnitudes between 4.0 – 4.9 , and 56 of magnitudes between 3.0 – 3.9. The largest aftershock occurred at 5.45 pm, April 21 at Lushan. The 5.4-magnitude aftershock occurred at the junction of the two peaks.
Location	–
Time	2013-04-21 18:38
ForwardCount	10
CommentCount	5
LikeCount	1
Keyword	Ya'an Earthquake
Province	Sichuan
City	Chengdu

4. Quality control and assessment

When the body of the message retrieved was removed from Sino-Weibo, we then removed this data entry from our dataset accordingly. Data without time information was also removed in the process of quality control. In addition, information with hyperlinks only or without valuable information was removed from our dataset. An example is shown below:

“# Ya’an earthquake in Sichuan # # microblogging topic details: web links, # Ya’an earthquake in Sichuan # Details: web links, # Ya’an 7 earthquake # # microblogging topic details: web link, # Ya’an 7 earthquake # Details: Web links, # Ya’an 7 earthquake # #, Ya’an earthquake microblogging reported safe # #.”

5. Value and significance

As time goes by, some messages retrieved have now been deleted by their bloggers, which makes it impossible to access some valuable messages posted at that time. As the only dataset that collects information about the 2013 Ya'an Earthquake, this dataset provides essential resources from Sina-Weibo for studying social media responses to the earthquake of the time.

Sina-Weibo provides a platform through which the public can communicate with others. With the development of the Internet in recent years, there has been in particular a large surge in the number of phone application users, and people are more and more concerned about hot news and events. Sina-Weibo, as a major Chinese microblogging platform, plays a crucial role in the search and dissemination of hot information, especially in the event of an earthquake. This dataset can be used by academics to study the types of information most easily forwarded, commented, liked, the ways of information dissemination and data content categorization, and so on.

Acknowledgments

This work is supported by the National Key Research and Development Program of China (2016YFE0122600). We thank Dr. Pang Lushen from the Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences for his suggestions on the collection of this dataset. Thank Li Zhenyu from Shandong University of Science and Technology for his support on data processing.

Ya’an Earthquake, available at: <https://en.wikipedia.org/wiki/2013_Lushan_earth

+ CSCD · Baidu Scholar

quake>.

+ CSCD · Baidu Scholar

Sina-Weibo, available at: <https://en.wikipedia.org/wiki/Sina_Weibo>.

+ CSCD · Baidu Scholar

Sutton J, Palen L & Irina S. Backchannels on the front lines: Emergent use of social media in the 2007 Southern California Fires, Proceedings of the Information Systems for Crisis Response and Management Conference (ISCRAM 2008), Washington, DC, 2008.

+ CSCD · Baidu Scholar

Glaser M. California wildfire coverage by local media, blogs, Twitter, maps and more. PBS MediaShift. Available at: <http://mediashift.org/2007/10/california-wildfire-coverage-by-local-media-blogs-twitter-maps-and-more298/>.

+ CSCD · Baidu Scholar

Vieweg S, Hughes AL, Starbird K et al. Microblogging during two natural hazards events: What twitter may contribute to situational awareness, Proc. CHI (2010): 1079 – 1088.

+ CSCD · Baidu Scholar

Qu Y, Wu PF & Wang X. Online community response to major disaster: A study of Tianya Forum in the 2008 Sichuan Earthquake, Proc. HICCS, 2009.

+ CSCD · Baidu Scholar

Qu Y, Huang C, Zhang P et al. Microblogging after a major disaster in China: A case study of the 2010 Yushu Earthquake, Proc. CSCW, 2011.

+ CSCD · Baidu Scholar

Li J, He Z, Plaza J et al. Social media: New perspectives to improve remote sensing for emergency response, Proceedings of the IEEE 105 (2017): 1900 – 1912.

+ CSCD · Baidu Scholar

Reuter C, Hughes AL & Kaufhold MA. Social media in crisis management: An evaluation and analysis of crisis informatics research, International Journal of Human–Computer Interaction 34 (2018): 280 – 294.

+ CSCD · Baidu Scholar

10.

Williams BD, Valero JN & Kim K. Social media, trust, and disaster: Does trust in public and nonprofit organizations explain social media use during a disaster? Quality & Quantity 52 (2018): 537 – 550.

+ CSCD · Baidu Scholar

11.

Park HW. YouTubers’ networking activities during the 2016 South Korea earthquake, Quality & Quantity 52 (2018): 1057 – 1068.

+ CSCD · Baidu Scholar

Data citation

1. Tian C, Li G, Yang T et al. A dataset of Ya'an Earthquake based on social media. Science Data Bank. DOI: 10.11922/sciencedb.560

稿件与作者信息

How to cite this article

Tian C, Li G, Yang T et al. A dataset of Ya'an Earthquake based on social media. China Scientific Data 3 (2018), DOI: 10.11922/csdata.2018.0004.en

Tian Chuanzhao

social media data collection and analysis, writing.

PhD; research area: disaster data mining.

Li Guoqing

advice on dataset design and data check, writing.

ligq@radi.ac.cn

PhD, Professor, research area: geospatial data infrastructure, remote sensing, big data.

Yang Tengfei

motivation of the research, writing.

PhD; research area: natural language processing, disaster information mining.

Li Zhenyu

data processing.

MSc; research area: data mining.

National Key Research and Development Program of China (2016YFE0122600)

出版历史

I区发布时间：2018年3月14日（版本EN1）

II区出版时间：2018年6月22日（版本EN2）

最近更新时间：2018年6月22日（版本EN3）