Extending Alexander’s ecological dominance-social competition (EDSC) evolutional model

Alexander’s Ecological Dominance and Social Competition (EDSC) model currently provides the most comprehensive overview of human traits in the development of a theory of human evolution and sociality (Alexander, 1990; Finn, Geary & Ward, 2005; Irons, 2005). His model provides a basis for explaining the evolution of human socio-cognitive abilities. Our paper examines the extension of Alexander’s model to incorporate the human trait of information behavior in synergy with ecological dominance and social competition as a human socio-cognitive competence. This paper discusses the various interdisciplinary perspectives exploring how evolution has shaped information behavior and why information behavior is emerging as an important human socio-cognitive competence. This paper outlines these issues, including the extension of Spink and Currier’s (2006a,b) evolution of information behavior model towards a more integrated understanding of how information behaviors have evolved (Spink & Cole, 2006).

Extending Alexander’s ecological dominance-social competition model : information behavior adaptation

Alexander’s Ecological Dominance and Social Competition (EDSC) model currently provides the most comprehensive overview of human traits in the development of a theory of human evolution and sociality (Alexander, 1990; Finn, Geary & Ward, 2005; Irons, 2005). His model provides a basis for explaining the evolution of human socio-cognitive abilities. Our paper examines the extension of Alexander’s model to incorporate the human trait of information behavior in synergy with ecological dominance and social competition as a human socio-cognitive competence. This paper discusses the various interdisciplinary perspectives exploring how evolution has shaped information behavior and why information behavior is emerging as an important human socio-cognitive competence. This paper outlines these issues, including the extension of Spink and Currier’s (2006a,b) evolution of information behavior model towards a more integrated understanding of how information behaviors have evolved (Spink & Cole, 2006).

Improving matching process in social network

Online dating networks, a type of social network, are gaining popularity. With many people joining and being available in the network, users are overwhelmed with choices when choosing their ideal partners. This problem can be overcome by utilizing recommendation methods. However, traditional recommendation methods are ineffective and inefficient for online dating networks where the dataset is sparse and/or large and two-way matching is required. We propose a methodology by using clustering, SimRank to recommend matching candidates to users in an online dating network. Data from a live online dating network is used in evaluation. The success rate of recommendation obtained using the proposed method is compared with baseline success rate of the network and the performance is improved by double.