An integrated design method of the compliant linear positioning device (CLPD) was researched, whi... more An integrated design method of the compliant linear positioning device (CLPD) was researched, which was composed of a compliant guide mechanism and two electromagnetic actuators. Typically, the actuators are designed after the compliant mechanism, which may make it more complex to improve the performances of the CLPD. With the utilization of the multi-physics co-simulation technology, established a parametric multi-physics finite element model (MFEM) of the CLPD including the compliant linear guide mechanism and the electromagnetic actuators simultaneously in the COMSOL environment. Proposed the constraints of the dominant parameters, based on the analysis of their influence on the characteristics of the CLPD. Then an integrated optimizing design strategy of the CLPD was put forward. According to the strategy, a two degree of freedom long-range linear compliant mechanism and its matching actuators were designed. The experimental results showed the performance of the designed CLPD, w...
We study a system in which N agents have to decide between two strategies θi(i ∈ 1 … N), for defe... more We study a system in which N agents have to decide between two strategies θi(i ∈ 1 … N), for defection or cooperation, when interacting with other n agents (either spatial neighbors or randomly chosen ones). After each round, they update their strategy responding nonlinearly to two different information sources: (i) the payoff ai(θi, fi) received from the strategic interaction with their n counterparts, (ii) the fraction fi of cooperators in this interaction. For the latter response, we assume social herding, i.e., agents adopt their strategy based on the frequencies of the different strategies in their neighborhood, without taking into account the consequences of this decision. We note that fi already determines the payoff, so there is no additional information assumed. A parameter ζ defines to what level agents take the two different information sources into account. For the strategic interaction, we assume a Prisoner's Dilemma game, i.e., one in which defection is the evoluti...
Massive data from software repositories and collaboration tools are widely used to study social a... more Massive data from software repositories and collaboration tools are widely used to study social aspects in software development. One question that several recent works have addressed is how a software project’s size and structure in uence team productivity, a question famously considered in Brooks’ law. Recent studies using massive repository data suggest that developers in larger teams tend to be less productive than smaller teams. Despite using similar methods and data, other studies argue for a positive linear or even super-linear relationship between team size and productivity, thus contesting the view of software economics that software projects are diseconomies of scale. In our work, we study challenges that can explain the disagreement between recent studies of developer productivity in massive repository data. We further provide, to the best of our knowledge, the largest, curated corpus of GitHub projects tailored to investigate the in uence of team size and collaboration pa...
Wisdom of crowds refers to the phenomenon that the ag-gregate prediction or forecast of a group o... more Wisdom of crowds refers to the phenomenon that the ag-gregate prediction or forecast of a group of individuals can be surprisingly more accurate than most individuals in the group, and sometimes – than any of the individuals comprising it. This article models the impact of social influence on the wisdom of crowds. We build a minimal-istic representation of individuals as Brownian particles coupled by means of social influence. We demonstrate that the model can reproduce results of a previous em-pirical study. This allows us to draw more fundamental conclusions about the role of social influence: In particu-lar, we show that the question of whether social influence has a positive or negative net effect on the wisdom of crowds is ill-defined. Instead, it is the starting config-uration of the population, in terms of its diversity and accuracy, that directly determines how beneficial social influence actually is. The article further examines the scenarios under which social influence pr...
We empirically analyze five online communities: Friendster, Livejournal, Facebook, Orkut, Myspace... more We empirically analyze five online communities: Friendster, Livejournal, Facebook, Orkut, Myspace, to identify causes for the decline of social networks. We define social resilience as the ability of a community to withstand changes. We do not argue about the cause of such changes, but concentrate on their impact. Changes may cause users to leave, which may trigger further leaves of others who lost connection to their friends. This may lead to cascades of users leaving. A social network is said to be resilient if the size of such cascades can be limited. To quantify resilience, we use the k-core analysis, to identify subsets of the network in which all users have at least k friends. These connections generate benefits (b) for each user, which have to outweigh the costs (c) of being a member of the network. If this difference is not positive, users leave. After all cascades, the remaining network is the k-core of the original network determined by the cost-to-benefit (c/b) ratio. By ...
Wisdom of crowds refers to the phenomenon that the aggregate prediction or forecast of a group of... more Wisdom of crowds refers to the phenomenon that the aggregate prediction or forecast of a group of individuals can be surprisingly more accurate than most individuals in the group, and sometimes { than any of the individuals comprising it. This article models the impact of social inuence on the wisdom of crowds. We build a minimalistic representation of individuals as Brownian particles coupled by means of social inuence. We demonstrate that the model can reproduce results of a previous empirical study. This allows us to draw more fundamental conclusions about the role of social inuence: In particular, we show that the question of whether social inuence has a positive or negative net eect on the wisdom of crowds is ill-dened. Instead, it is the starting conguration of the population, in terms of its diversity and accuracy, that directly determines how benecial social inuence actually is. The article further examines the scenarios under which social inuence promotes or impairs the wis...
How do humans respond to indirect social influence when making decisions? We analysed an experime... more How do humans respond to indirect social influence when making decisions? We analysed an experiment where subjects had to repeatedly guess the correct answer to factual questions, while having only aggregated information about the answers of others. While the response of humans to aggregated information is a widely observed phenomenon, it has not been investigated quantitatively, in a controlled setting. We found that the adjustment of individual guesses depends linearly on the distance to the mean of all guesses. This is a remarkable, and yet surprisingly simple, statistical regularity. It holds across all questions analysed, even though the correct answers dier in several orders of magnitude. Our finding supports the assumption that individual diversity does not aect the response to indirect social influence. It also complements previous results on the nonlinear response in information-rich scenarios. We argue that the nature of the response to social influence crucially changes w...
We propose an agent-based model of collective opinion formation to study the wisdom of crowds und... more We propose an agent-based model of collective opinion formation to study the wisdom of crowds under social influence. The opinion of an agent is a continuous positive value, denoting its subjective answer to a factual question. The wisdom of crowds states that the average of all opinions is close to the truth, i.e., the correct answer. But if agents have the chance to adjust their opinion in response to the opinions of others, this effect can be destroyed. Our model investigates this scenario by evaluating two competing effects: (1) agents tend to keep their own opinion (individual conviction), (2) they tend to adjust their opinion if they have information about the opinions of others (social influence). For the latter, two different regimes (full information vs. aggregated information) are compared. Our simulations show that social influence only in rare cases enhances the wisdom of crowds. Most often, we find that agents converge to a collective opinion that is even farther away f...
We analyze an agent-based model to estimate how the costs and benefits of users in an online soci... more We analyze an agent-based model to estimate how the costs and benefits of users in an online social network (OSN) impact the robustness of the OSN. Benefits are measured in terms of relative reputation that users receive from their followers. They can be increased by direct and indirect reciprocity in following each other, which leads to a core-periphery structure of the OSN. Costs relate to the effort to login, to maintain the profile, etc. and are assumed as constant for all users. The robustness of the OSN depends on the entry and exit of users over time. Intuitively, one would expect that higher costs lead to more users leaving and hence to a less robust OSN. We demonstrate that an optimal cost level exists, which maximizes both the performance of the OSN, measured by means of the long-term average benefit of its users, and the robustness of the OSN, measured by means of the lifetime of the core of the OSN. Our mathematical and computational analyses unfold how changes in the co...
Leading-following behaviour in Bechstein's bats transfers information about suitable roost si... more Leading-following behaviour in Bechstein's bats transfers information about suitable roost sites from experienced to inexperienced individuals, and thus ensures communal roosting. We analyze 9 empirical data sets about individualized leading-following (L/F) events, to infer rules that likely determine the formation of L/F pairs. To test these rules, we propose five models that differ regarding the empirical information taken into account to form L/F pairs: activity of a bat in exploring possible roosts, tendency to lead and to follow. The comparison with empirical data was done by constructing social networks from the observed L/F events, on which centralities were calculated to quantify the importance of individuals in these L/F networks. The centralities from the empirical network are then compared for statistical differences with the model-generated centralities obtained from 105 model realizations. We find that two models perform well in comparison with the empirical data: O...
Leading-following behavior as a way of transferring information about the location of resources i... more Leading-following behavior as a way of transferring information about the location of resources is widespread in different animal societies. However, it cannot always be observed directly. Here, we develop a general method to infer leading-following events from observational data if only the discrete appearance of individuals is recorded. Our method further allows to distinguish such events from local enhancement at the resource, such as swarming behavior in case of bats, which is another widespread way of transferring information among animals. To test our methodology, we analyze longitudinal data about the roosting behavior of Bechstein's bats from two different colonies and different years. The detection of leading-following events allows us, in a second step, to construct social networks in which nodes represent individual bats and directed and weighted links the leading-following events. We analyze the topology of these networks on the level of the colony, to see whether al...
An integrated design method of the compliant linear positioning device (CLPD) was researched, whi... more An integrated design method of the compliant linear positioning device (CLPD) was researched, which was composed of a compliant guide mechanism and two electromagnetic actuators. Typically, the actuators are designed after the compliant mechanism, which may make it more complex to improve the performances of the CLPD. With the utilization of the multi-physics co-simulation technology, established a parametric multi-physics finite element model (MFEM) of the CLPD including the compliant linear guide mechanism and the electromagnetic actuators simultaneously in the COMSOL environment. Proposed the constraints of the dominant parameters, based on the analysis of their influence on the characteristics of the CLPD. Then an integrated optimizing design strategy of the CLPD was put forward. According to the strategy, a two degree of freedom long-range linear compliant mechanism and its matching actuators were designed. The experimental results showed the performance of the designed CLPD, w...
We study a system in which N agents have to decide between two strategies θi(i ∈ 1 … N), for defe... more We study a system in which N agents have to decide between two strategies θi(i ∈ 1 … N), for defection or cooperation, when interacting with other n agents (either spatial neighbors or randomly chosen ones). After each round, they update their strategy responding nonlinearly to two different information sources: (i) the payoff ai(θi, fi) received from the strategic interaction with their n counterparts, (ii) the fraction fi of cooperators in this interaction. For the latter response, we assume social herding, i.e., agents adopt their strategy based on the frequencies of the different strategies in their neighborhood, without taking into account the consequences of this decision. We note that fi already determines the payoff, so there is no additional information assumed. A parameter ζ defines to what level agents take the two different information sources into account. For the strategic interaction, we assume a Prisoner's Dilemma game, i.e., one in which defection is the evoluti...
Massive data from software repositories and collaboration tools are widely used to study social a... more Massive data from software repositories and collaboration tools are widely used to study social aspects in software development. One question that several recent works have addressed is how a software project’s size and structure in uence team productivity, a question famously considered in Brooks’ law. Recent studies using massive repository data suggest that developers in larger teams tend to be less productive than smaller teams. Despite using similar methods and data, other studies argue for a positive linear or even super-linear relationship between team size and productivity, thus contesting the view of software economics that software projects are diseconomies of scale. In our work, we study challenges that can explain the disagreement between recent studies of developer productivity in massive repository data. We further provide, to the best of our knowledge, the largest, curated corpus of GitHub projects tailored to investigate the in uence of team size and collaboration pa...
Wisdom of crowds refers to the phenomenon that the ag-gregate prediction or forecast of a group o... more Wisdom of crowds refers to the phenomenon that the ag-gregate prediction or forecast of a group of individuals can be surprisingly more accurate than most individuals in the group, and sometimes – than any of the individuals comprising it. This article models the impact of social influence on the wisdom of crowds. We build a minimal-istic representation of individuals as Brownian particles coupled by means of social influence. We demonstrate that the model can reproduce results of a previous em-pirical study. This allows us to draw more fundamental conclusions about the role of social influence: In particu-lar, we show that the question of whether social influence has a positive or negative net effect on the wisdom of crowds is ill-defined. Instead, it is the starting config-uration of the population, in terms of its diversity and accuracy, that directly determines how beneficial social influence actually is. The article further examines the scenarios under which social influence pr...
We empirically analyze five online communities: Friendster, Livejournal, Facebook, Orkut, Myspace... more We empirically analyze five online communities: Friendster, Livejournal, Facebook, Orkut, Myspace, to identify causes for the decline of social networks. We define social resilience as the ability of a community to withstand changes. We do not argue about the cause of such changes, but concentrate on their impact. Changes may cause users to leave, which may trigger further leaves of others who lost connection to their friends. This may lead to cascades of users leaving. A social network is said to be resilient if the size of such cascades can be limited. To quantify resilience, we use the k-core analysis, to identify subsets of the network in which all users have at least k friends. These connections generate benefits (b) for each user, which have to outweigh the costs (c) of being a member of the network. If this difference is not positive, users leave. After all cascades, the remaining network is the k-core of the original network determined by the cost-to-benefit (c/b) ratio. By ...
Wisdom of crowds refers to the phenomenon that the aggregate prediction or forecast of a group of... more Wisdom of crowds refers to the phenomenon that the aggregate prediction or forecast of a group of individuals can be surprisingly more accurate than most individuals in the group, and sometimes { than any of the individuals comprising it. This article models the impact of social inuence on the wisdom of crowds. We build a minimalistic representation of individuals as Brownian particles coupled by means of social inuence. We demonstrate that the model can reproduce results of a previous empirical study. This allows us to draw more fundamental conclusions about the role of social inuence: In particular, we show that the question of whether social inuence has a positive or negative net eect on the wisdom of crowds is ill-dened. Instead, it is the starting conguration of the population, in terms of its diversity and accuracy, that directly determines how benecial social inuence actually is. The article further examines the scenarios under which social inuence promotes or impairs the wis...
How do humans respond to indirect social influence when making decisions? We analysed an experime... more How do humans respond to indirect social influence when making decisions? We analysed an experiment where subjects had to repeatedly guess the correct answer to factual questions, while having only aggregated information about the answers of others. While the response of humans to aggregated information is a widely observed phenomenon, it has not been investigated quantitatively, in a controlled setting. We found that the adjustment of individual guesses depends linearly on the distance to the mean of all guesses. This is a remarkable, and yet surprisingly simple, statistical regularity. It holds across all questions analysed, even though the correct answers dier in several orders of magnitude. Our finding supports the assumption that individual diversity does not aect the response to indirect social influence. It also complements previous results on the nonlinear response in information-rich scenarios. We argue that the nature of the response to social influence crucially changes w...
We propose an agent-based model of collective opinion formation to study the wisdom of crowds und... more We propose an agent-based model of collective opinion formation to study the wisdom of crowds under social influence. The opinion of an agent is a continuous positive value, denoting its subjective answer to a factual question. The wisdom of crowds states that the average of all opinions is close to the truth, i.e., the correct answer. But if agents have the chance to adjust their opinion in response to the opinions of others, this effect can be destroyed. Our model investigates this scenario by evaluating two competing effects: (1) agents tend to keep their own opinion (individual conviction), (2) they tend to adjust their opinion if they have information about the opinions of others (social influence). For the latter, two different regimes (full information vs. aggregated information) are compared. Our simulations show that social influence only in rare cases enhances the wisdom of crowds. Most often, we find that agents converge to a collective opinion that is even farther away f...
We analyze an agent-based model to estimate how the costs and benefits of users in an online soci... more We analyze an agent-based model to estimate how the costs and benefits of users in an online social network (OSN) impact the robustness of the OSN. Benefits are measured in terms of relative reputation that users receive from their followers. They can be increased by direct and indirect reciprocity in following each other, which leads to a core-periphery structure of the OSN. Costs relate to the effort to login, to maintain the profile, etc. and are assumed as constant for all users. The robustness of the OSN depends on the entry and exit of users over time. Intuitively, one would expect that higher costs lead to more users leaving and hence to a less robust OSN. We demonstrate that an optimal cost level exists, which maximizes both the performance of the OSN, measured by means of the long-term average benefit of its users, and the robustness of the OSN, measured by means of the lifetime of the core of the OSN. Our mathematical and computational analyses unfold how changes in the co...
Leading-following behaviour in Bechstein's bats transfers information about suitable roost si... more Leading-following behaviour in Bechstein's bats transfers information about suitable roost sites from experienced to inexperienced individuals, and thus ensures communal roosting. We analyze 9 empirical data sets about individualized leading-following (L/F) events, to infer rules that likely determine the formation of L/F pairs. To test these rules, we propose five models that differ regarding the empirical information taken into account to form L/F pairs: activity of a bat in exploring possible roosts, tendency to lead and to follow. The comparison with empirical data was done by constructing social networks from the observed L/F events, on which centralities were calculated to quantify the importance of individuals in these L/F networks. The centralities from the empirical network are then compared for statistical differences with the model-generated centralities obtained from 105 model realizations. We find that two models perform well in comparison with the empirical data: O...
Leading-following behavior as a way of transferring information about the location of resources i... more Leading-following behavior as a way of transferring information about the location of resources is widespread in different animal societies. However, it cannot always be observed directly. Here, we develop a general method to infer leading-following events from observational data if only the discrete appearance of individuals is recorded. Our method further allows to distinguish such events from local enhancement at the resource, such as swarming behavior in case of bats, which is another widespread way of transferring information among animals. To test our methodology, we analyze longitudinal data about the roosting behavior of Bechstein's bats from two different colonies and different years. The detection of leading-following events allows us, in a second step, to construct social networks in which nodes represent individual bats and directed and weighted links the leading-following events. We analyze the topology of these networks on the level of the colony, to see whether al...
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