期刊,Computational & mathematical organization theory 2025年31卷2期_国家学术搜索

Social cybersecurity in 2023: a review of the 16th annual SBP-BRiMS conference

Robert ThomsonAryn Pyke

105-108页

查看更多>>摘要：Increasing amounts of digital data, embedded sensors that collecting human information, rapidly changing communication media, changes in legislation concerning digital rights and privacy, spread of 4 G technology to developing countries and development of 5 G technology, the rise of large language models, and other changes are creating a new cyber-mediated world in which the very precepts of why, when, and how people interact and make decisions is being called into question. The goal of this conference is to build this new community of social cyber scholars by bringing together and fostering interaction between members of the scientific, corporate, government and military communities, who are interested in understanding, forecasting, and impacting human sociocultural behavior. Fortunately, as the papers in this volume illustrate, this community is poised to answer these challenges. In this special issue, we recognize the best conference papers, as well as the best challenge problem submissions. These six papers represent some of the breadth of work presented at the 16th Annual SBP-BRiMS Conference (2023).

原文链接:

NETL
NSTL
Springer Nature

Social cybersecurity in 2023: a review of the 16th annual SBP-BRiMS conference

Robert ThomsonAryn Pyke

105-108页

查看更多>>摘要：Increasing amounts of digital data, embedded sensors that collecting human information, rapidly changing communication media, changes in legislation concerning digital rights and privacy, spread of 4 G technology to developing countries and development of 5 G technology, the rise of large language models, and other changes are creating a new cyber-mediated world in which the very precepts of why, when, and how people interact and make decisions is being called into question. The goal of this conference is to build this new community of social cyber scholars by bringing together and fostering interaction between members of the scientific, corporate, government and military communities, who are interested in understanding, forecasting, and impacting human sociocultural behavior. Fortunately, as the papers in this volume illustrate, this community is poised to answer these challenges. In this special issue, we recognize the best conference papers, as well as the best challenge problem submissions. These six papers represent some of the breadth of work presented at the 16th Annual SBP-BRiMS Conference (2023).

原文链接:

NETL
NSTL
Springer Nature

Misogynistic targeting of women in power predicts broader online harassment patterns

Jennifer Golbeck

109-119页

查看更多>>摘要：Online harassment is a well-documented and studied problem on social media. Who does this harassing, how, and to what degree are important questions that can inform platform policies and automated controls as well as helping understand harassers more broadly. This study investigates users who were discovered because they created a post that harassed a women in power using misogynistic slurs. Do these tend to be isolated incidents, or do such users engage in higher rates of harassment more generally? Findings from Twitter, Parler, and Reddit suggest that this population uses offensive slurs at several times the rate of control groups. We break down these findings and discuss the implications for moderation, automation, user well-being, and platform success.

原文链接:

NETL
NSTL
Springer Nature

Misogynistic targeting of women in power predicts broader online harassment patterns

Jennifer Golbeck

109-119页

查看更多>>摘要：Online harassment is a well-documented and studied problem on social media. Who does this harassing, how, and to what degree are important questions that can inform platform policies and automated controls as well as helping understand harassers more broadly. This study investigates users who were discovered because they created a post that harassed a women in power using misogynistic slurs. Do these tend to be isolated incidents, or do such users engage in higher rates of harassment more generally? Findings from Twitter, Parler, and Reddit suggest that this population uses offensive slurs at several times the rate of control groups. We break down these findings and discuss the implications for moderation, automation, user well-being, and platform success.

原文链接:

NETL
NSTL
Springer Nature

Investigating the use of belief-bias to measure acceptance of false information

Robert ThomsonWilliam Frangia

120-138页

查看更多>>摘要：Belief-bias occurs when individuals' prior beliefs impact their ability to judge the validity (i.e., structure) of an argument such that they are predisposed to accept conclusions consistent with their prior beliefs regardless of the argument's validity. The present study uses a minimal explanation paradigm to evaluate how United States Military Academy cadets assess the validity of arguments surrounding the pull-out from Afghanistan presented by different sources of authority. Participants exhibited a significantly greater likelihood of rejecting an invalid argument with true facts compared to accepting a valid argument with false facts, with overconfidence scores implying they were unaware of this difficulty in reasoning. We also found that participants were were more critical of arguments about US capabilities coming from civilian sources. Results from the HEXACO personality assessment showed that task performance was positively correlated with perfectionism and inquisitiveness sub-scales, implying that those high in those measures were less likely to exhibit belief-bias. Even when factoring-in these traits, results revealed a small yet significant trend for participants to reject valid arguments from their peers compared with senior military and civilian counterparts. Overall, the present study shows a differential impact of belief-bias on true vs false facts, that this is influenced by the underlying source of the argument, and that personality traits mediate these effects.

原文链接:

NETL
NSTL
Springer Nature

Investigating the use of belief-bias to measure acceptance of false information

Robert ThomsonWilliam Frangia

120-138页

查看更多>>摘要：Belief-bias occurs when individuals' prior beliefs impact their ability to judge the validity (i.e., structure) of an argument such that they are predisposed to accept conclusions consistent with their prior beliefs regardless of the argument's validity. The present study uses a minimal explanation paradigm to evaluate how United States Military Academy cadets assess the validity of arguments surrounding the pull-out from Afghanistan presented by different sources of authority. Participants exhibited a significantly greater likelihood of rejecting an invalid argument with true facts compared to accepting a valid argument with false facts, with overconfidence scores implying they were unaware of this difficulty in reasoning. We also found that participants were were more critical of arguments about US capabilities coming from civilian sources. Results from the HEXACO personality assessment showed that task performance was positively correlated with perfectionism and inquisitiveness sub-scales, implying that those high in those measures were less likely to exhibit belief-bias. Even when factoring-in these traits, results revealed a small yet significant trend for participants to reject valid arguments from their peers compared with senior military and civilian counterparts. Overall, the present study shows a differential impact of belief-bias on true vs false facts, that this is influenced by the underlying source of the argument, and that personality traits mediate these effects.

原文链接:

NETL
NSTL
Springer Nature

Characterizing the roles of preference homophily and network structure on outcomes of consensus games

Pratyush AryaNisheeth Srivastava

139-160页

查看更多>>摘要：This paper presents results from in silico experiments trying to uncover the mechanisms by which people both succeed and fail to reach consensus in networked games, for network structures produced by a variety of generative mechanisms. We find that the primary cause for failure in such games is preferential selection of information sources. Agents forced to sample information from randomly selected fixed neighborhoods eventually converge to a consensus, while agents free to form their own neighborhoods and forming them on the basis of homophily frequently end up creating balkanized cliques. Small-world structure attenuates the drive towards consensus in fixed networks, but not in self-selecting networks. Preferentially attached networks show the highest convergence to consensus, thereby showing resilience to balkanization even in self-selecting networks. We investigate the reasons for such behavior by altering graph properties of generated networks. We conclude with a brief discussion of the implications of our findings for representing behavior in socio-cultural modeling.

原文链接:

NETL
NSTL
Springer Nature

Characterizing the roles of preference homophily and network structure on outcomes of consensus games

Pratyush AryaNisheeth Srivastava

139-160页

查看更多>>摘要：This paper presents results from in silico experiments trying to uncover the mechanisms by which people both succeed and fail to reach consensus in networked games, for network structures produced by a variety of generative mechanisms. We find that the primary cause for failure in such games is preferential selection of information sources. Agents forced to sample information from randomly selected fixed neighborhoods eventually converge to a consensus, while agents free to form their own neighborhoods and forming them on the basis of homophily frequently end up creating balkanized cliques. Small-world structure attenuates the drive towards consensus in fixed networks, but not in self-selecting networks. Preferentially attached networks show the highest convergence to consensus, thereby showing resilience to balkanization even in self-selecting networks. We investigate the reasons for such behavior by altering graph properties of generated networks. We conclude with a brief discussion of the implications of our findings for representing behavior in socio-cultural modeling.

原文链接:

NETL
NSTL
Springer Nature

Modeling and analyzing network dynamics of COVID-19 vaccine information propagation in the Chinese Sina Microblog

Fulian YinJinxia WangHongyu PangXin Pei...

161-180页

查看更多>>摘要：Information about the vaccine is usually spread through heterogeneous networks in reality, where public opinion bursts out faster than in homogeneous networks. Considering the complexity of heterogeneous networks, we develop a network suscep-tible-forwarding-immune (NET-SFI) model to describe the patterns of information propagation in the actual social network. Classifying the states of nodes according to the number of users can contact in the social network, the NET-SFI model focuses on the network structure and user heterogeneity. We adopt a data-model drive method to conduct the model validation including two types of COVID-19 vaccine information from the Chinese Sina Microblog. Our parameter sensitivity analyses show the important significance of node degree in causing the outbreak of public opinion. Moreover, corresponding conclusions based on our analytic study are conducive to designing valid strategies for vaccine information dissemination.

原文链接:

NETL
NSTL
Springer Nature

Modeling and analyzing network dynamics of COVID-19 vaccine information propagation in the Chinese Sina Microblog

Fulian YinJinxia WangHongyu PangXin Pei...

161-180页

查看更多>>摘要：Information about the vaccine is usually spread through heterogeneous networks in reality, where public opinion bursts out faster than in homogeneous networks. Considering the complexity of heterogeneous networks, we develop a network suscep-tible-forwarding-immune (NET-SFI) model to describe the patterns of information propagation in the actual social network. Classifying the states of nodes according to the number of users can contact in the social network, the NET-SFI model focuses on the network structure and user heterogeneity. We adopt a data-model drive method to conduct the model validation including two types of COVID-19 vaccine information from the Chinese Sina Microblog. Our parameter sensitivity analyses show the important significance of node degree in causing the outbreak of public opinion. Moreover, corresponding conclusions based on our analytic study are conducive to designing valid strategies for vaccine information dissemination.

原文链接:

NETL
NSTL
Springer Nature