In recent years,with the rapid growth of social network services(SNS),social networks pervade nearly every aspect of our daily lives.Social networks are influencing today’s societal and cultural issues,and changing t...In recent years,with the rapid growth of social network services(SNS),social networks pervade nearly every aspect of our daily lives.Social networks are influencing today’s societal and cultural issues,and changing the way of people seeing themselves.To fully understand the running mechanisms of social networks,in this paper,we aim at series of high knitted and important elements of online social networks.We mainly focus on 3 important but also open research problems,they are(1)structural properties and evolving laws,(2)social crowds and their interaction behaviors and(3)information and its diffusion.In this paper,we review the related work on the 3 problems.Then,we briefly introduce some interesting research directions and our progress on these research problems.展开更多
A composite random variable is a product (or sum of products) of statistically distributed quantities. Such a variable can represent the solution to a multi-factor quantitative problem submitted to a large, diverse, i...A composite random variable is a product (or sum of products) of statistically distributed quantities. Such a variable can represent the solution to a multi-factor quantitative problem submitted to a large, diverse, independent, anonymous group of non-expert respondents (the “crowd”). The objective of this research is to examine the statistical distribution of solutions from a large crowd to a quantitative problem involving image analysis and object counting. Theoretical analysis by the author, covering a range of conditions and types of factor variables, predicts that composite random variables are distributed log-normally to an excellent approximation. If the factors in a problem are themselves distributed log-normally, then their product is rigorously log-normal. A crowdsourcing experiment devised by the author and implemented with the assistance of a BBC (British Broadcasting Corporation) television show, yielded a sample of approximately 2000 responses consistent with a log-normal distribution. The sample mean was within ~12% of the true count. However, a Monte Carlo simulation (MCS) of the experiment, employing either normal or log-normal random variables as factors to model the processes by which a crowd of 1 million might arrive at their estimates, resulted in a visually perfect log-normal distribution with a mean response within ~5% of the true count. The results of this research suggest that a well-modeled MCS, by simulating a sample of responses from a large, rational, and incentivized crowd, can provide a more accurate solution to a quantitative problem than might be attainable by direct sampling of a smaller crowd or an uninformed crowd, irrespective of size, that guesses randomly.展开更多
When a crowdsourcing approach is used to assist the classification of a set of items,the main objective is to classify this set of items by aggregating the worker-provided labels.A secondary objective is to assess the...When a crowdsourcing approach is used to assist the classification of a set of items,the main objective is to classify this set of items by aggregating the worker-provided labels.A secondary objective is to assess the workers’skill levels in this process.A classical model that achieves both objectives is the famous Dawid-Skene model.In this paper,we consider a third objective in this context,namely,to learn a classifier that is capable of labelling future items without further assistance of crowd workers.By extending the DawidSkene model to include the item features into consideration,we develop a Classification-Oriented Dawid Skene(CODS)model,which achieves the three objectives simultaneously.The effectiveness of CODS on this three dimensions of the problem space is demonstrated experimentally.展开更多
Rioting historically has been known to cause changes in individual cognition, with heightened emotionality, increased excitement and reduced reflective thought. A cross-disciplinary literature review hypothesises emot...Rioting historically has been known to cause changes in individual cognition, with heightened emotionality, increased excitement and reduced reflective thought. A cross-disciplinary literature review hypothesises emotional states generate corresponding metabolic bio magnetic fields that radiate in patterns reflecting these emotional states. The oscillatory phase of these waves is advanced as being more significant than the power of signal, permitting stochastic effects to magnify signals by appropriating ambient noise. Possible transmission and detection structures in the body are discussed, induced paramagnetic sensitivity in crowd participants in a phase transition process is hypothesised, the effect may be proportional to crowd numbers. It is suspected that positive effects seen in Transcranial Magnetic Therapy used to treat depression may be operating on this mechanism, acting on natural receptors in the limbic system which also capture light and are implicated in mood transitions. A number of paramagnetic neurotransmitters may be implicated.展开更多
基金supported by National BasicResearch Program of China(2013CB329601 and 2013CB329606)the National Natural Science Foundation of China(91124002,61372191,and 61303190)
文摘In recent years,with the rapid growth of social network services(SNS),social networks pervade nearly every aspect of our daily lives.Social networks are influencing today’s societal and cultural issues,and changing the way of people seeing themselves.To fully understand the running mechanisms of social networks,in this paper,we aim at series of high knitted and important elements of online social networks.We mainly focus on 3 important but also open research problems,they are(1)structural properties and evolving laws,(2)social crowds and their interaction behaviors and(3)information and its diffusion.In this paper,we review the related work on the 3 problems.Then,we briefly introduce some interesting research directions and our progress on these research problems.
文摘A composite random variable is a product (or sum of products) of statistically distributed quantities. Such a variable can represent the solution to a multi-factor quantitative problem submitted to a large, diverse, independent, anonymous group of non-expert respondents (the “crowd”). The objective of this research is to examine the statistical distribution of solutions from a large crowd to a quantitative problem involving image analysis and object counting. Theoretical analysis by the author, covering a range of conditions and types of factor variables, predicts that composite random variables are distributed log-normally to an excellent approximation. If the factors in a problem are themselves distributed log-normally, then their product is rigorously log-normal. A crowdsourcing experiment devised by the author and implemented with the assistance of a BBC (British Broadcasting Corporation) television show, yielded a sample of approximately 2000 responses consistent with a log-normal distribution. The sample mean was within ~12% of the true count. However, a Monte Carlo simulation (MCS) of the experiment, employing either normal or log-normal random variables as factors to model the processes by which a crowd of 1 million might arrive at their estimates, resulted in a visually perfect log-normal distribution with a mean response within ~5% of the true count. The results of this research suggest that a well-modeled MCS, by simulating a sample of responses from a large, rational, and incentivized crowd, can provide a more accurate solution to a quantitative problem than might be attainable by direct sampling of a smaller crowd or an uninformed crowd, irrespective of size, that guesses randomly.
基金supported in part by the National Key R&D Program of China(2021ZD0110700)in part by the Fundamental Research Funds for the Central Universities,in part by the State Key Laboratory of Software Development Environmentin part by a Leverhulme Trust Research Project Grant.
文摘When a crowdsourcing approach is used to assist the classification of a set of items,the main objective is to classify this set of items by aggregating the worker-provided labels.A secondary objective is to assess the workers’skill levels in this process.A classical model that achieves both objectives is the famous Dawid-Skene model.In this paper,we consider a third objective in this context,namely,to learn a classifier that is capable of labelling future items without further assistance of crowd workers.By extending the DawidSkene model to include the item features into consideration,we develop a Classification-Oriented Dawid Skene(CODS)model,which achieves the three objectives simultaneously.The effectiveness of CODS on this three dimensions of the problem space is demonstrated experimentally.
文摘Rioting historically has been known to cause changes in individual cognition, with heightened emotionality, increased excitement and reduced reflective thought. A cross-disciplinary literature review hypothesises emotional states generate corresponding metabolic bio magnetic fields that radiate in patterns reflecting these emotional states. The oscillatory phase of these waves is advanced as being more significant than the power of signal, permitting stochastic effects to magnify signals by appropriating ambient noise. Possible transmission and detection structures in the body are discussed, induced paramagnetic sensitivity in crowd participants in a phase transition process is hypothesised, the effect may be proportional to crowd numbers. It is suspected that positive effects seen in Transcranial Magnetic Therapy used to treat depression may be operating on this mechanism, acting on natural receptors in the limbic system which also capture light and are implicated in mood transitions. A number of paramagnetic neurotransmitters may be implicated.
