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People generate online content everyday at every hour at social networks. Social networks are a medium in which people can give their opinion on different topics and obtain new information. The content people create can be useful for researchers to understand human behavior in cities such as Quito. In this work, we are going to describe how Quito city is described on the travel network TripAdvisor...
Because the existing location recommendation algorithms in Location-based Social Networks have the characteristic of high time complexity and low recommendation accuracy, a new location recommendation algorithm based on temporal and geographical similarity is proposed by improving the traditional location recommendation algorithm in this paper. New recommendation algorithm has innovation mainly in...
In this paper, we develop an algorithm to cluster places not only based on their locations but also their semantics. Specifically, two places are considered similar if they are spatially close and visited by people of similar communities. With the explosion in the availability of location-tracking technologies, it has become easy to track locations and movements of users through user "check-ins"...
In our prior work, we identified rules for use in recommendation algorithms on Online Social Network (OSN) in order to increase the relevance of content suggested to a user. The resulting recommendation algorithms filter out and prioritize event types for OSN users (such as photo posts by friends, status posts, shared content, etc.), and are thereby intended to reduce information overload. This paper...
Roles and positions are structural components in complex social systems which group actors based on how similarly they are connected to the rest of the actors. Role and position detection methods have been successfully used to evaluate and understand the dynamics of social networks and the behavior of their members. However, actor similarities used to detect positions have been based on pairwise comparisons...
Discovering topologies in a social network targets various business applications such as finding key influencers in a network, recommending music movies in virtual communities, finding active groups in network and promoting a new product. Since social networks are large in size, discovering topologies from such networks is challenging. In this paper, we present a scalable topology discovery approach...
The economic development of a region is closely related with its population flow from/to other regions. And the regions, which have close relationship of the population flow, usually have a high economic relationship. Therefore, the analysis of the regional population flow can find the potential economic circles. Different from previous methods which are only rely on the analysis of experts to find...
Despites the great interest caused by social networks in Business Science, their analysis is rarely performed both in a global and systematic way in this field: most authors focus on parts of the studied network, or on a few nodes considered individually. This could be explained by the fact that practical extraction of social networks is a difficult and costly task, since the specific relational data...
Blogs have become a typical online publication in Web2.0 era. The users of blogs interact with each other by publishing entries, reading and posting comments to other's entries, and discussing with friends. By these actions, information propagates from user to user on the social networks. This paper extracts the information flow hidden in entries and investigates the rules of information flow in both...
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