Information Cascades in Social Media During Emergencies
The article linked above studies how information spreads on social media in response to an emergency. By analyzing data on Twitter activity during an RPI emergency, the researchers were able to identify certain information cascades and patterns to see how information spreads on Twitter. They found that during an emergency, activity on Twitter displays more signs of information sharing and broadcasting activities such as retweets rather than direct replies to spread information. As we learned in class, information cascades have the potential to occur when people make decisions sequentially and later people watch the actions of the earlier people to infer something about what the earlier people know. The cascade develops when people abandon their own information in favor of inferences based on earlier people’s actions. In this paper, the information cascades happen when users ”follow” the information source and retweet the message because they are influenced or believe the information from another user. This act of retweeting helps spread information throughout Twitter as people make the decision to pass on information that they feel is important for others to know.
The article described a general model of diffusion of information to provide context to how Twitter’s network works and how information cascades can form on Twitter. In this network, nodes may receive info from various nodes and they evaluate the information they receive and perform various actions such as sharing the information.The weighted edges between the nodes represent the social relationships between the nodes that are based on the likelihood that a message will be believed as it is passed from one node to another. This is similar to the idea of tie strength that we covered in class. There are both strong and weak ties on Twitter that form based on the amount and type of a user’s interaction. In a way, a user will be more willing to believe in the information that another person posts if the user has a stronger tie with that person. This relates to the article’s model because they mentioned this concept of trust as a factor in a user’s decision to believe in the information and retweet the message. The passing of information along this network causes information cascades as users retweet messages that they have been influenced by and believe in.
The researchers studied a specific emergency that happened in the RPI community to analyze the form of these information cascades more closely. They found that most of these information cascades originated from local media users and specific users from the RPI community. The cascades tended to be wide, but not very long as only a small number of distinct retweeted messages were passed onto a large audience. This information relates to what we learned in class as it demonstrates an application of information cascades in real life. As the paper concluded that emergency managers can use the information flow found to facilitate the spreading of accurate information and minimize inaccurate information, it shows how information cascades can be utilized to improve the world. For example, users with a high in-degree reflect that the user may be a reliable source or provide valuable information since their messages are frequently shared with others. In the study, the local media, RPI staff and a RPI student organization had the highest in-degree, showing that it is important for emergency management to make announcements on social media so the community can get accurate information about a situation. The study used information about social media and information cascades, which are concepts that we learned in class, and applied it specifically to emergencies, so that their findings can be used by emergency responders to best share information about an emergency to the general public.