Looking at Social Media Reactions After Terrorist Attack

How do people from distant communities react just after a terrorist attack? As they reach out through social media, how do they show their support and express their own fears?

These were some of the questions pursued by researchers from the University of Pittsburgh and Cornell University. In the first large-scale analysis of its kind, researchers analyzed Twitter posts from the hours and weeks following the 2013 Boston Marathon bombing.

The findings, published in the journal EPJ Data Science, show the extent to which the communities outside of Boston expressed their emotions and how these reactions correlated with geographic proximity, social-network connections, and direct ties to Boston.

The results may help government agencies understand how best to handle public fear following a tragic event.

“When a community in one geographic location is attacked, it is important for government officials to be able to predict where public fears will be heightened most as a result of that attack,” said lead researcher Yu-Ru Lin, an assistant professor in Pitt’s School of Information Sciences.

“The findings of our study will potentially assist officials in predicting the exact manner and extent in which citizens in their own regions will react to tragic occurrences in another region of the country.”

Previous research on emotional responses to terror attacks has only focused on those in directly affected areas. For the new study, however, researchers were able to gauge reactions from 95 cities around the world through the analysis of more than 180 million geocoded tweets (posts) on Twitter.

This included the 60 most-populated metropolitan areas in the United States as well as the 35 highest-populated cities outside of the United States.

To study expressions of fear, the researchers used content-analysis programs to search for a predetermined set of keywords — such as “fearful,” “fatal,” and “terror” — in tweets directly related to the bombing. They also utilized Twitter hashtags to identify tweets expressing feelings of solidarity and sympathy.

The findings showed that citizens in certain cities were more likely to express specific emotions based on geography and shared experiences.

The hashtag #PrayForBoston — a variant of the #PrayFor{X} hashtag that has been used in recent years following various tragic events — was used to measure expressions of sympathy.

Citizens in London were reserved in their expressions of fear and solidarity but were more forthcoming in their use of the #PrayForBoston hashtag. The researchers suggest that the greater show of sympathy from Londoners was due to the citizens of London having endured their own terrorist attacks in the recent past and therefore relating to what they were going through.

The hashtag #BostonStrong — a variant of the #{X}strong hashtags made popular by Lance Armstrong’s Livestrong motto and the U.S. Army’s “Army Strong” media campaign — was used to measure expressions of solidarity. Expressions of solidarity were used most by citizens in U.S. cities that have close geographic proximity or similar cultural identities to Boston.

“Our findings suggest that the immediate emotional reactions on social media are indicators of deeper feelings of connection to suffering in other communities that linger,” said Drew Margolin, Ph.D., an assistant professor of communication in the College of Agriculture and Life Sciences at Cornell University.

“In the future, this may have implications for anticipating how communities will respond to shocking events beyond terrorist attacks, such as school shootings, natural disasters like Hurricane Sandy, or incidents like those that occurred in Ferguson, Missouri.”

Finally, the extent to which communities outside of the Boston metropolitan area expressed emotional reactions to the attack directly correlated with geographic proximity, social network connections to Boston residents, and relationships to the city of Boston.

The extent to which individuals had ties to the Boston area was the best predictor of fear and solidarity expression as well as a strong predictor of an expression of sympathy.

Source: University of Pittsburgh