Online dating sites are growing steadily in popularity, despite challenging economic times. In addition, online dating sites are facing increasing competition for their services from free social networking sites. Desp...Online dating sites are growing steadily in popularity, despite challenging economic times. In addition, online dating sites are facing increasing competition for their services from free social networking sites. Despite these harsh economic times and the increasing competition, online dating websites have continued to increase in popularity. This growth justifies the need to better understand how these volitional and paid websites have been so successful. By addressing the call for research in emergent information systems （IS） contexts, this study proposes a theoretical framework for investigation in a purely volitional website context. A framework based on the DeLone and McLean＇s IS success model is developed. Implications for practice and research are discussed.展开更多
Potential behavior prediction involves understanding the latent human behavior of specific groups,and can assist organizations in making strategic decisions.Progress in information technology has made it possible to a...Potential behavior prediction involves understanding the latent human behavior of specific groups,and can assist organizations in making strategic decisions.Progress in information technology has made it possible to acquire more and more data about human behavior.In this paper,we examine behavior data obtained in realworld scenarios as an information network composed of two types of objects(humans and actions)associated with various attributes and three types of relationships(human-human,human-action,and action-action),which we call the heterogeneous behavior network(HBN).To exploit the abundance and heterogeneity of the HBN,we propose a novel network embedding method,human-action-attribute-aware heterogeneous network embedding(a4 HNE),which jointly considers structural proximity,attribute resemblance,and heterogeneity fusion.Experiments on two real-world datasets show that this approach outperforms other similar methods on various heterogeneous information network mining tasks for potential behavior prediction.展开更多
The function of a network is affected by its structure. For example, the presence of highly interactive individuals, or hubs, influences the extent and rate of information spread across a network. In a network of inte...The function of a network is affected by its structure. For example, the presence of highly interactive individuals, or hubs, influences the extent and rate of information spread across a network. In a network of interactions, the duration over which individual variation in interactions persists may affect how the network operates. Individuals may persist in their behavior over time and across situations, often referred to as personality. Colonies of social insects are an example of a biological system in which the structure of the coordinated networks of interacting workers may greatly influence information flow within the colony, and therefore its collective behavior. Here I investigate the effects of persistence in walking patterns on interaction networks us- ing computer simulations that are parameterized using observed behavior of harvester ants. I examine how the duration of persis- tence in spatial behavior influences network structure. Furthermore, I explore how spatial features of the environment affect the relationship between persistent behavior and network structure. I show that as persistence increases, the skewness of the weighted degree distribution of the interaction network increases. However, this relationship holds only when ants are confined in a space with boundaries, but not when physical barriers are absent. These findings suggest that the influence of animal personalities on network structure and function depends on the environment in which the animals reside [Current Zoology 61 （1）： 98-106, 2015].展开更多
Stanley Milgram's small world experiment presents "six degrees of separation" of our world.One phenomenon of the experiment still puzzling us is that how individuals operating with the social network inf...Stanley Milgram's small world experiment presents "six degrees of separation" of our world.One phenomenon of the experiment still puzzling us is that how individuals operating with the social network information with their characteristics can be very adept at finding the short chains. The previous works on this issue focus whether on the methods of navigation in a given network structure,or on the effects of additional information to the searching process. In this paper, the authors emphasize that the growth and shape of network architecture is tightly related to the individuals' attributes. The authors introduce a method to reconstruct nodes' intimacy degree based on local interaction. Then we provide an intimacy based approach for orientation in networks. The authors find that the basic reason of efficient search in social networks is that the degree of "intimacy" of each pair of nodes decays with the length of their shortest path exponentially. Meanwhile, the model can explain the hubs limitation which was observed in real-world experiment.展开更多
文摘Online dating sites are growing steadily in popularity, despite challenging economic times. In addition, online dating sites are facing increasing competition for their services from free social networking sites. Despite these harsh economic times and the increasing competition, online dating websites have continued to increase in popularity. This growth justifies the need to better understand how these volitional and paid websites have been so successful. By addressing the call for research in emergent information systems （IS） contexts, this study proposes a theoretical framework for investigation in a purely volitional website context. A framework based on the DeLone and McLean＇s IS success model is developed. Implications for practice and research are discussed.
基金Project supported by the National Natural Science Foundation of China(Nos.U1509206,61625107,and U1611461)the Key Program of Zhejiang Province,China(No.2015C01027).
文摘Potential behavior prediction involves understanding the latent human behavior of specific groups,and can assist organizations in making strategic decisions.Progress in information technology has made it possible to acquire more and more data about human behavior.In this paper,we examine behavior data obtained in realworld scenarios as an information network composed of two types of objects(humans and actions)associated with various attributes and three types of relationships(human-human,human-action,and action-action),which we call the heterogeneous behavior network(HBN).To exploit the abundance and heterogeneity of the HBN,we propose a novel network embedding method,human-action-attribute-aware heterogeneous network embedding(a4 HNE),which jointly considers structural proximity,attribute resemblance,and heterogeneity fusion.Experiments on two real-world datasets show that this approach outperforms other similar methods on various heterogeneous information network mining tasks for potential behavior prediction.
文摘The function of a network is affected by its structure. For example, the presence of highly interactive individuals, or hubs, influences the extent and rate of information spread across a network. In a network of interactions, the duration over which individual variation in interactions persists may affect how the network operates. Individuals may persist in their behavior over time and across situations, often referred to as personality. Colonies of social insects are an example of a biological system in which the structure of the coordinated networks of interacting workers may greatly influence information flow within the colony, and therefore its collective behavior. Here I investigate the effects of persistence in walking patterns on interaction networks us- ing computer simulations that are parameterized using observed behavior of harvester ants. I examine how the duration of persis- tence in spatial behavior influences network structure. Furthermore, I explore how spatial features of the environment affect the relationship between persistent behavior and network structure. I show that as persistence increases, the skewness of the weighted degree distribution of the interaction network increases. However, this relationship holds only when ants are confined in a space with boundaries, but not when physical barriers are absent. These findings suggest that the influence of animal personalities on network structure and function depends on the environment in which the animals reside [Current Zoology 61 （1）： 98-106, 2015].
基金supported by the National Natural Science Foundation of China under Grant Nos.61203156,61374175,and 61573065
文摘Stanley Milgram's small world experiment presents "six degrees of separation" of our world.One phenomenon of the experiment still puzzling us is that how individuals operating with the social network information with their characteristics can be very adept at finding the short chains. The previous works on this issue focus whether on the methods of navigation in a given network structure,or on the effects of additional information to the searching process. In this paper, the authors emphasize that the growth and shape of network architecture is tightly related to the individuals' attributes. The authors introduce a method to reconstruct nodes' intimacy degree based on local interaction. Then we provide an intimacy based approach for orientation in networks. The authors find that the basic reason of efficient search in social networks is that the degree of "intimacy" of each pair of nodes decays with the length of their shortest path exponentially. Meanwhile, the model can explain the hubs limitation which was observed in real-world experiment.
