It's possible to predict some violent public protests by tracking social media posts on moral outrage over a triggering event. Tracy Le Blanc/Pexels

Every grade school teacher knows that student conduct can get out of hand, fast, when a group of kids eggs on one individual. Time-outs are a testimony to the power of isolating one 10-year-old from a choir of buddies.

Social media plays a role similar to a gang of hyped-up grade schoolers, providing a community that can express collective disapproval of people or events. When this disapproval has a moral cast ⁠— for example, after a police shooting or the removal of a statue ⁠— the social network's particular characteristics are key predictors about whether that disapproval will turn violent.

There is a word for the way group support of a belief system makes it seem worth fighting for: moralization. Tracking social network activity now makes it possible to measure the chances for an individual belief to become moralized by a group ⁠— a phenomenon known as moral convergence.

In a recent study in Nature, Rice Business professor Marlon Mooijman, then at the Kellogg School of Management, joined a team that analyzed when and how violence erupts in protests. In a series of observation and behavior experiments that mixed psychology, organizational theory and computer science, they accurately predicted how violence is influenced by group discussion of moral views on social media.

The researchers started by studying the number and content of tweets linked to the Baltimore riots in 2015, after the death of Freddie Gray in police custody. The researchers then compared these tweets with the number of arrests in a given time frame, using a methodology developed by Marlon Mooijman and Joe Hoover from the Brain and Creativity Institute at the University of Southern California.

To analyze the tweets responding to Gray's death, they first separated them into two sets: Those with moral commentary and those without moral judgments.

Next, the researchers tracked whether tweets with moral content increased on days with violent protests. Violence was measured using the number of police arrests, which the researchers compared with the specific time frames of moral tweets.

There was no major difference in the overall tweet traffic discussing Freddie Gray's death on days with violent protests and on peaceful days. The number of moralizing tweets, however, clearly correlated with episodes of violent protests, rising to nearly double the moralizing tweets on days with no violence.

This raised a provocative question. Were morally ⁠— based tweets a response to the events of the day ⁠— or were they somehow driving the violence?

To find out, Mooijman and Hoover worked with computer scientists Ying Lin and Jeng Ji of Rensselaer Polytechnic Institute and Morteza Dehghani of the University of Southern California to develop algorithms that could establish mathematical probabilities for the results.

For every single-unit increase in moral tweets over a 4-hour period, the researchers found, there was a .25 corresponding increase in arrests.

The researchers then tried to measure the effect similar moral views ⁠— such as a social media page with self-selected members of a similar political affiliation ⁠— had on violence during protests.

To do so, they set up a second study, which measured participant reactions to the protestors of a far-right rally in Charlottesville, Virginia in 2017. Participants ranked their level of agreement over the morality of protesting the rally.

There was a direct relationship between believing a protest action was moral, the researchers found, and finding violence at that protest acceptable. This relationship held true throughout the study, regardless of political orientation.

The researchers' next goal was to identify the impact of exposure to people of like beliefs. To do this, participants rated their feelings when they were told that most people in the U.S. shared their views. While the intensity of participants' moral views created the potential for violence, the researchers found, violence resulted when only actively validated by others with similar views.

Having one's moral outrage supported by others on social media, the professors concluded, may explain the spike in violence in recent protests.

While respect for privacy remains critical, governments and law enforcement can use the social media trend to pinpoint the moments when moral outrage can turn deadly. Perhaps most importantly, however, the research also suggests practical tactics for calming violent tendencies before they get out of control. To reduce real-life protest violence, they wrote, it's critical that social media sites include a variety of voices. It's another reason, if any were needed, that a bit of judicious exposure to other views is healthy for everyone.

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This story originally ran on Rice Business Wisdom.

Marlon Mooijman is an assistant professor of Organizational Behavior. He teaches in the undergraduate business minor program and MBA full-time program.

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How Houston innovators played a role in the historic Artemis II splashdown

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Research from Rice University played a critical role in the safe return of U.S. astronauts aboard NASA’s Artemis II mission this month.

Rice mechanical engineer Tayfun E. Tezduyar and longtime collaborator Kenji Takizawa developed a key computational parachute fluid-structure interaction (FSI) analysis system that proved vital in NASA’s Orion capsule’s descent into the Pacific Ocean. The FSI system, originally developed in 2013 alongside NASA Johnson Space Center, was critical in Orion’s three-parachute design, which slowed the capsule as it returned to Earth, according to Rice.

The model helped ensure that the parachute design was large enough to slow the capsule for a safe landing while also being stable enough to prevent the capsule from oscillating as it descended.

“You cannot separate the aerodynamics from the structural dynamics,” Tezduyar said in a news release. “They influence each other continuously and even more so for large spacecraft parachutes, so the analysis must capture that interaction in a robustly coupled way.”

The end result was a final parachute system, refined through NASA drop tests and Rice’s computational FSI analysis, that eliminated fluctuations and produced a stable descent profile.

Apart from the dynamic challenges in design, modeling Orion’s parachutes also required solving complex equations that considered airflow and fabric deformation and accounted for features like ringsail canopy construction and aerodynamic interactions among multiple parachutes in a cluster.

“Essentially, my entire group was dedicated to that work, because I considered it a national priority,” Tezduyar added in the release. “Kenji and I were personally involved in every computer simulation. Some of the best graduate students and research associates I met in my career worked on the project, creating unique, first-of-its-kind parachute computer simulations, one after the other.”

Current Intuitive Machines engineer Mario Romero also worked on Orion during his time at NASA. From 2018 to 2021, Romero was a member of the Orion Crew Capsule Recovery Team, which focused on creating likely scenarios that crewmembers could encounter in Orion.

The team trained in NASA’s 6.2-million-gallon pool, using wave machines to replicate a range of sea conditions. They also simulated worst-case scenarios by cutting the lights, blasting high-powered fans and tipping a mock capsule to mimic distress situations. In some drills, mock crew members were treated as “injured,” requiring the team to practice safe, controlled egress procedures.

“It’s hard to find the appropriate descriptors that can fully encapsulate the feeling of getting to witness all the work we, and everyone else, did being put into action,” Romero tells InnovationMap. “I loved seeing the reactions of everyone, but especially of the Houston communities—that brought me a real sense of gratitude and joy.”

Intuitive Machines was also selected to support the Artemis II mission using its Space Data Network and ground station infrastructure. The company monitored radio signals sent from the Orion spacecraft and used Doppler measurements to help determine the spacecraft's precise position and speed.

Tim Crain, Chief Technology Officer at Intuitive Machines, wrote about the experience last week.

"I specialized in orbital mechanics and deep space navigation in graduate school,” Crain shared. “But seeing the theory behind tracking spacecraft come to life as they thread through planetary gravity fields on ultra-precise trajectories still seems like magic."

UH breakthrough moves superconductivity closer to real-world use

Energy Breakthrough

University of Houston researchers have set a new benchmark in the field of superconductivity.

Researchers from the UH physics department and the Texas Center for Superconductivity (TcSUH) have broken the transition temperature record for superconductivity at ambient pressure. The accomplishment could lead to more efficient ways to generate, transmit and store energy, which researchers believe could improve power grids, medical technologies and energy systems by enabling electricity to flow without resistance, according to a release from UH.

To break the record, UH researchers achieved a transition temperature 151 Kelvin, which is the highest ever recorded at ambient pressure since the discovery of superconductivity in 1911.

The transition temperature represents the point just before a material becomes superconducting, where electricity can flow through it without resistance. Scientists have been working for decades to push transition temperature closer to room temperature, which would make superconducting technologies more practical and affordable.

Currently, most superconductors must be cooled to extremely low temperatures, making them more expensive and difficult to operate.

UH physicists Ching-Wu Chu and Liangzi Deng published the research in the Proceedings of the National Academy of Sciences earlier this month. It was funded by Intellectual Ventures and the state of Texas via TcSUH and other foundations. Chu, founding director and chief scientist at TcSUH, previously made the breakthrough discovery that the material YBCO reaches superconductivity at minus 93 K in 1987. This helped begin a global competition to develop high-temperature superconductors.

“Transmitting electricity in the grid loses about 8% of the electricity,” Chu, who’s also a professor of physics at UH and the paper’s senior author, said in a news release. “If we conserve that energy, that’s billions of dollars of savings and it also saves us lots of effort and reduces environmental impacts.”

Chu and his team used a technique known as pressure quenching, which has been adapted from techniques used to create diamonds. With pressure quenching, researchers first apply intense pressure to the material to enhance its superconducting properties and raise its transition temperature.

Next, researchers are targeting ambient-pressure, room-temperature superconductivity of around 300 K. In a companion PNAS paper, Chu and Deng point to pressure quenching as a promising approach to help bridge the gap between current results and that goal.

“Room-temperature superconductivity has been seen as a ‘holy grail’ by scientists for over a century,” Rohit Prasankumar, director of superconductivity research at Intellectual Ventures, said in the release. “The UH team’s result shows that this goal is closer than ever before. However, the distance between the new record set in this study and room temperature is still about 140 C. Closing this gap will require concerted, intentional efforts by the broader scientific community, including materials scientists, chemists, and engineers, as well as physicists.”

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This article originally appeared on EnergyCapitalHTX.com.