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1) Find a case study showing how social media can be used for situational awareness, instruction or preparedness activities and discuss.

Qu, Y., Huang, C., Zhang, P., & Zhang, J. (2011, March). Microblogging after a major disaster in China: a case study of the 2010 Yushu earthquake. In Proceedings of the ACM 2011 conference on Computer supported cooperative work (pp. 25-34). ACM.

This is a case study on how Chinese internet users used microblogging during the 2010 Yushu Earthquake in China and thereby tried to understand what role microblogging played in disaster response. They analyzed the content of the message, the trends at the time, the process of spreading the information and how different messages were developed over time. Sina Weibo, a popular Chinese microblogging website, was the social media medium chosen for this study. Microblogging is a type of social media with unique features such as the 140-character limit, easy accessibility, and light-weight operations which are mainly used for social interaction and informational purposes. Twitter is another example of microblogging.

The 2010 Yushu Earthquake occurred in Yushu, Qinghai province, China, on April 14, 2010. The magnitude was 7.1 M according to the China Earthquake Administration (CEA). There were 2,698 people confirmed dead, 270 missing, and thousands more injured and homeless. During that time, in addition to the non-stop news coverage, the event also swept social media sites in China. “Netizens” on various online portals responded to the disaster by seeking and sharing information, expressing their feelings and opinions, and organizing donation and relief activities. Among them, Sina Weibo became the most active social medium for these activities. About 94,101 microblog posts and 41,817 re-posts related to the Earthquake during the first 48 hours immediately after impact were collected and analyzed from Sino Weibo.

For each of the microblog messages, basic information including the author’s name, message content, publication date, and the total number of re-posts of the message was extracted. The profiles of the authors of these messages and related information, including the number of messages the author posted or re-posted, the number of followers, the number of followees, and whether the author is a certified VIP member were scanned. “Certified VIP” is a feature of this app that is similar to the “verified accounts” of Twitter, that is basically exclusive for well-known celebrity, government agencies, and brands.

After the data was collected, the study explored the following 3 questions:

Q1: What kinds of messages do people post after a major disaster? (To analyze the content)

Q2: Are there different posting and re-posting behaviors in respect to different types of information and different phases during the disaster response period? (To analyze the trends of different types of messages)

Q3: How does disaster-related information spread in a microblogging system? (to study the information spread by examining the re-posting patterns)

The results showed that microblogging was mainly used for situation updates, opinion expression, emotional support, and calling for action. A large amount of situation update messages were posted immediately after the earthquake. Action-related messages were typically related to disaster rescue and relief efforts. People used the social platform to disseminate disaster relief related information and to call for and coordinate actions, including requesting rescue and relief resources, organizing rescue and relief activities, and organizing donation campaigns. These messages were not posted immediately but after gaining sufficient understanding of the situation. As for the spread of information, it was found that the situation update messages were re-posted faster compared to any other type of messages, while opinion related messages spread slower than any other type of messages.

One limitation of this study was in the data collection. They could collect microblog messages only with two keywords in the content analysis, which made the content analysis biased toward some specific categories. However, this study basically laid a foundation for further studies into cross-cultural comparisons between Sin-Weibo and Twitter to study different socio-cultural systems and how that effects message content, trends, information spreading, as well as the role of authorized accounts such as Government agencies and other agencies in information spreading and rescue efforts.

Retrieved from:

https://www.researchgate.net/publication/220878979...

2) Set up an aggregator or collector using one of the free tools to monitor a topic or area

Trendsmap is basically a new mash-up of Twitter, Google Maps and What The Trend app that maps out Twitter trends at a local level. That is, it takes Twitter trends and maps them out all the way to a local level, and thereby, see what Twitter users are talking about in real time for instance, in London, New York, LA etc. The app consists of tag clouds that float over the region on the map and by clicking on any of them, a small info box pops up that aggregates the latest tweets, a description of that trend, local and global seven-day histories of that trend's popularity, volume of tweets for that word as well as some top-related news links that change depending on what's trending. Although, one disadvantage of this app is that it doesn’t serve smaller towns and rural areas.

https://www.cnet.com/news/trendsmap-maps-twitter-t...

https://www.trendsmap.com/