Tracking Storms of Misinformation Spread Amid Disasters

Tracking storms of misinformation spread amid disasters

ISE Magazine September 2019 Volume: 51 Number: 9

By Kyle Hunt, Puneet Agarwal and Jun Zhuang

https://www.iise.org/iemagazine/2019-09/html/hunt/hunt.html

Over the last decade, social media has been increasingly employed for sharing opinions, personal up-dates and breaking news. Platforms such as Twitter and Facebook allow for the delivery of important information at extreme speeds, facilitating the efficient dissemination of content to millions of users around the world.

Given these benefits, social media platforms are often used to spread emergency communications such as evacuation plans, shelter information and weather updates. During natural disasters, acts of terrorism, chemical threats and other crisis situations, millions of people around the world turn to social media to get the information they need to stay current during plight situations.

Unfortunately, due to the unmoderated nature of social media, misinformation has plagued the networks of platforms such as Twitter. In the last few years, “fake news” has been a trending phrase and topic across mass media, often identified in politics and other controversial domains. Misinformation and fake news are also spread across social media when information integrity is crucial to the safety of the public, such as during natural and manmade disasters. During these events, timely and credible information is of the utmost importance to those affected by the disasters, and also those following the disaster-related news.

Examples of misinformation during disasters

On April 15, 2013, the United States was struck by an act of terrorism when two homemade pressure cooker bombs were detonated near the finish line of the Boston Marathon, killing three people and significantly injuring hundreds more. During the chaos that ensued, many false rumors were spread. One of the most prominent stated that an 8-year-old girl was killed in the bombings while she was running in remembrance of the 2012 Sandy Hook school shooting victims.

Another false rumor took direct advantage of Twitter. A fake account named @_BostonMarathon was created and posted a tweet which read “For every retweet we receive we will donate $1.00 to the #BostonMarathon victims.” Many users ended up retweeting the post, believing it would aid recovery efforts. In fact, the account was not created to donate money. Twitter eventually suspended the fraudulent account and warnings were spread to look out for similar accounts. Be-tween these two cases, millions of Twitter users were exposed to false information.

On May 22, 2017, singer Ariana Grande was performing in the Manchester Arena in England. When the concert concluded and attendees were beginning to leave the venue, a suicide bomber detonated explosives attached to his body. The bombing led to 23 deaths and 139 injuries, the deadliest terrorist attack in England since the 2005 London bombings. After the bombing, a rumor was spread on Twitter and Facebook claiming that unaccompanied children were being taken to safety at the local Holiday Inn. Soon after the rumor was spread, a Holiday Inn representative made a statement informing the public that the rumor was false; there were no unaccompanied children at the hotel.

On Aug. 25, 2017, Hurricane Harvey made landfall in Texas. During the storm, there was legislation due to be passed in Texas concerning immigration policies. As some people began to inquire about eligibility requirements at evacuation shelters, a false rumor began to proliferate throughout social media and Texas that shelters were going to check IDs. This rumor proved to be dangerous as many undocumented immigrants were afraid to go to shelters due to the potential threat of deportation.

On the heels of Hurricane Harvey, Hurricane Irma was generating immense damage across the Caribbean on its path toward Florida. On Sept. 10, 2017, Irma made landfall in Cud-joe Key, Florida, bringing deadly storm surges and rainfall. Before Irma’s landfall, a sheriff in Florida posted on Twitter saying that he would be checking identifications at evacuation centers in his jurisdictional county. Although the sheriff did not spread false information, many inferred that he was checking IDs to primarily scare undocumented immigrants from seeking safety in those shelters, and this false rumor began to spread both online and offline. The sheriff later clarified his tweet, reassuring the community that he was not targeting the immigrant population. Many additional tweets were posted by other agencies and accounts in order to help comfort the population and deliver the correct information.

The plethora of evidence showing the spread of misinformation during disasters is proof that social media users should proceed with caution when believing, posting or reposting information on these platforms. In many cases, major govern-mental and nongovernmental organizations choose to intervene when misinformation is spread in order to provide the public with updated and valid information.

The importance of major agencies, verified users

In most cases, misinformation propagates throughout social media and other online platforms at extreme speeds, reaching millions of people around the world. Given this threat, social media consumers need timely and valid information to create a safer online and offline environment. In most cases, the postings that debunk misinformation are made by major governmental organizations and, in some cases, nongovernmental organizations.

When false rumors were spread that undocumented immigrants could not enter shelters during both Hurricane Harvey and Hurricane Irma, many agencies posted to Twitter in order to comfort the public and offer correct information. Some governmental agencies that posted include the Federal Emergency Management Agency (FEMA), the United States Department of Homeland Security Customs and Border Protection (DHS CBP), DHS Immigration and Customs Enforcement (ICE), and the cities of Houston and Miami.

Many news organizations also posted information to let the population know that it was safe to seek shelter, including The Miami Herald, The Washington Post, CNN and The Hill, among many others. Governmental officials, such as Houston Mayor Sylvester Turner, also had to make public announcements in order to disprove the threatening information.

Likewise, in the Manchester Arena (2017) and Boston Marathon (2013) bombings, many agencies, celebrities and public figures made announcements and postings to debunk the misinformation that penetrated social media platforms.

Research has shown that it is the verified users (those acknowledged by Twitter as accounts of public interest) who receive the most interaction when posting misinformation de-bunking messages. In many cases, more than 100,000 users interact with these postings by retweeting, liking and commenting on the content. This behavior helps to further spread the accurate and needed information through Twitter’s network.

Likewise, many users and agencies cite information from external sources, such as news websites and government web-sites, in order to offer credibility in their misinformation de-bunking posts. This information is vital to the safety of social media platforms.

For Hurricanes Sandy (2012), Maria (2017), Harvey (2017), Irma (2017), Michael (2018) and Florence (2018), false rumors and misinformation were exposed on FEMA’s “Rumor Control” pages (see related story above). On these web pages created during or immediately after the hurricanes, FEMA keeps a record of hurricane-related false rumors and offers valid information alongside the different rumors. These web pages are important resources for the public and especially social media users to be aware of and explore before trusting disaster-related information.

Assisting agencies via machine learning

Due to the speed, breadth and depth of information diffusion across social media, it is increasingly important to develop and utilize tools that can assist in the monitoring of information and ultimately promote a safer online environment.

Technologies such as machine learning can be used to assist agencies in the tracking of misinformation. In many disasters, there are multiple false rumors being spread, and agencies have to choose which rumors to combat with their limited resources. A machine learning framework offers organizations and agencies a tool to track identified misinformation on platforms such as Twitter and make informed decisions on whether to use resources in an attempt to debunk the false information.

By collecting Twitter data from previous disasters where misinformation spread, machine learning models can be trained to learn which tweets are spreading true information, which are spreading false information and which contain opinions or comments on the subject matter

Supervised machine learning models as basic as random forests to more architecturally complicated models such as deep neural networks have performed with more than 90% accuracy in deciphering the differences between the different types of tweets. After training these models with enough historical data, they can be deployed to predict the veracity of newly emerging tweets

As misinformation is detected on social media, or even in offline social networks, agencies can deploy these trained machine learning models on livestream tweets. By querying a certain misinformation topic on Twitter and feeding these tweets to the models, the incoming tweets will be automatically labeled as true, false or other (consisting of opinions or comments). The agencies can then monitor the tweets and analyze how many users are spreading the false information, as well as how many users are posting true tweets regarding the false information.

If enough users are already posting valid information and few are continuing to spread falsehoods, the agency may choose not to use its resources to correct them. If many users are continuing to spread the misinformation and not many have posted the truth, the agency may choose to debunk the misinformation and clarify any confusion or rid any malicious intentions.

Machine learning offers a high speed, efficient method to facilitate this. As long as there is a demand for credible information, major emergency organizations and decision makers could benefit greatly from machine learning and its broad applications.

Improvements in disaster research and disaster practices, whether small or large, can make a significant impact on the lives of people around the world. Having knowledge and awareness of modern threats, such as false information spreading on social media platforms, can create a safer environment for the public.

Employing advanced technologies to improve the current state of disaster management can offer modern and dynamic solutions that are readily adoptable by agencies and companies around the world.