Human
Social Networks: Information Is 'Contagious' In Large Groups, Affects Recall Ability
Matt Hoffman
First Posted: Nov 16, 2015 11:56 AM EST
A team of researchers from Stony Brook University used an advanced computer model to examine the spreading of information in social situations, finding that the memory of one person can indirectly influence others through shared social connections.
Previous research has shown that multiple behaviors, like smoking, fads and fashion, obesity, and eyewitness testimony, spread quickly through social networks, but the driving force behind this spread of information and behaviors has remained shrouded in mystery. In order to examine the force behind this spread, the research team decided to use computer models that are capable of simulating groups that ranged from two people to 500, numbers much larger than the standard laboratory model.
"In large social networks, our model demonstrated that information is 'contagious' in much the same way that behavior seems to be contagious," Christian Luhmann and Suparna Rajaram of Stony Brook University said in a news release. "These results suggest that information transmission is a critical mechanism underlying the social transmission of behavior."
The team began with a simulation of information spreading in three-person groups, with each group member being programmed to be capable of memorizing and learning from information gathered from the other two members. This simulation was done in accordance with previous findings from past experiments done with real people, in order to closely and accurately reflect the actual memory process.
The study compared the three-person group to three individuals, taking each's ability to study and recall words provided to them. In total, 1,000 group-versus-individual simulation comparisons were made in the study.
The findings showed that information shared between the three-person collaborative group was able to recall significantly less when compared to the recall of the three individuals, directly mirroring the patterns of collective memory and information sharing seen among real people. This phenomenon of better recollection among groups is referred to as "collaborative inhibition," which occurs because, when in groups, individuals usually converge on similar information, which limits the amount of information that the group can learn in total.
This simulation was then expanded and rerun to examine groups from two to 128 members, with the results echoing those of the first test. The findings showed that with the more people introduced into the group, the more collaborative inhibition increased and affected the group. Each individual added to the group increased the groups overall recall ability, but caused the group to lag behind the efforts of that same amount of separated individuals. So, a group with seven members could recall more than a group with five, but that seven-person group still performed worse than each of the seven individuals working in isolation.
Once the group numbers exceeded seven people, the researchers saw that with each addition, the collaborative groups were slowly able to overcome the effects of collaborative inhibition, and the individuals began to peak in memory performance. These results showed that in small groups, there a limitations in information sharing that cannot be overcome by simply adding more members to the group.
With the large groups, Luhmann and Rajaram created a model that allowed individuals within the groups to interact with their "neighbors," as they would in realistic networks. These results showed that direct neighbors had more similar knowledge than indirect neighbors - those separated by more than one person. The further number of people apart neighbors were, the less similar their retained information was.
"We know that social influences on memory are complex, and yet our simplified model is sufficient to account for key findings from previous work, both within small groups and large social networks," Luhmann and Rajaram said. "Taken together, the findings of the current study leverage laboratory results and explanations to develop a much-needed theoretical account of behavior in large social networks."
The team believes that this study's findings, published in the Association for Psychological Science's journal Psychological Science, could show how information in the real world spreads contagiously among groups.
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TagsGroup learning, individual learning, Social networks, Social Networking, Stony Brook University, Contagious information, Social connections, Christian Luhmann, Suparna Rajaram, Memory process, Memory, group vs. individual learning, collaborative inhibition, memory performance, recall ability, Association for Psychological Science ©2024 ScienceWorldReport.com All rights reserved. Do not reproduce without permission. The window to the world of science news.
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First Posted: Nov 16, 2015 11:56 AM EST
A team of researchers from Stony Brook University used an advanced computer model to examine the spreading of information in social situations, finding that the memory of one person can indirectly influence others through shared social connections.
Previous research has shown that multiple behaviors, like smoking, fads and fashion, obesity, and eyewitness testimony, spread quickly through social networks, but the driving force behind this spread of information and behaviors has remained shrouded in mystery. In order to examine the force behind this spread, the research team decided to use computer models that are capable of simulating groups that ranged from two people to 500, numbers much larger than the standard laboratory model.
"In large social networks, our model demonstrated that information is 'contagious' in much the same way that behavior seems to be contagious," Christian Luhmann and Suparna Rajaram of Stony Brook University said in a news release. "These results suggest that information transmission is a critical mechanism underlying the social transmission of behavior."
The team began with a simulation of information spreading in three-person groups, with each group member being programmed to be capable of memorizing and learning from information gathered from the other two members. This simulation was done in accordance with previous findings from past experiments done with real people, in order to closely and accurately reflect the actual memory process.
The study compared the three-person group to three individuals, taking each's ability to study and recall words provided to them. In total, 1,000 group-versus-individual simulation comparisons were made in the study.
The findings showed that information shared between the three-person collaborative group was able to recall significantly less when compared to the recall of the three individuals, directly mirroring the patterns of collective memory and information sharing seen among real people. This phenomenon of better recollection among groups is referred to as "collaborative inhibition," which occurs because, when in groups, individuals usually converge on similar information, which limits the amount of information that the group can learn in total.
This simulation was then expanded and rerun to examine groups from two to 128 members, with the results echoing those of the first test. The findings showed that with the more people introduced into the group, the more collaborative inhibition increased and affected the group. Each individual added to the group increased the groups overall recall ability, but caused the group to lag behind the efforts of that same amount of separated individuals. So, a group with seven members could recall more than a group with five, but that seven-person group still performed worse than each of the seven individuals working in isolation.
Once the group numbers exceeded seven people, the researchers saw that with each addition, the collaborative groups were slowly able to overcome the effects of collaborative inhibition, and the individuals began to peak in memory performance. These results showed that in small groups, there a limitations in information sharing that cannot be overcome by simply adding more members to the group.
With the large groups, Luhmann and Rajaram created a model that allowed individuals within the groups to interact with their "neighbors," as they would in realistic networks. These results showed that direct neighbors had more similar knowledge than indirect neighbors - those separated by more than one person. The further number of people apart neighbors were, the less similar their retained information was.
"We know that social influences on memory are complex, and yet our simplified model is sufficient to account for key findings from previous work, both within small groups and large social networks," Luhmann and Rajaram said. "Taken together, the findings of the current study leverage laboratory results and explanations to develop a much-needed theoretical account of behavior in large social networks."
The team believes that this study's findings, published in the Association for Psychological Science's journal Psychological Science, could show how information in the real world spreads contagiously among groups.
Related Articles
Facebook: Quitting Can Lead To A Happier Life, Study Says
Science of Standing In Line: Who Goes First?
For more great science stories and general news, please visit our sister site, Headlines and Global News (HNGN).
See Now: NASA's Juno Spacecraft's Rendezvous With Jupiter's Mammoth Cyclone