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Current state-of-the-art in big social data analytics is largely limited to graph theoretical approaches such as social network analysis (SNA) informed by the social philosophical approach of relational sociology. This paper proposes and illustrates an alternate holistic approach to big social data analytics, social set analysis (SSA), which is based on the sociology of associations, mathematics of...
Diffusion Tensor Imaging (DTI) is an effective tool for the analysis of structural brain connectivity in normal development and in a broad range of brain disorders. However efforts to derive inherent characteristics of structural brain networks have been hampered by the very high dimensionality of the data, relatively small sample sizes, and the lack of widely acceptable connectivity-based regions...
This paper proposes a new method to classify tourist areas following specific characteristics. Indeed, we introduce some original computed indicators using social networks and administrative data. These 10 indicators are used to construct tourist area's profiles. We demonstrate in this paper that different tourist spots can then be grouped according to their profiles. Thus we present an original area...
Quantitative understanding of people's behaviors on social networks has significant meaning to reveal the origins of many socioeconomic phenomena. This paper focuses on the time characteristic of human behavior online. Four famous web forums of China were analyzed, including Sina, NetEase, HuBeiDongHu and LiXiang. The empirical analysis result presents some statistical features on the behaviors of...
Every year research institutions produce petabytes of data. Yet, only a small percent of the data is readily accessible for analysis. Terra Populus acts as the bridge between big data sources and researchers. Researchers are provided convenient web applications that allow them to access, analyze, and tabulate different datasets under a common platform. Terra Populus is developing three unique applications...
Microblogs play an important role in online social communications. Different from ordinary pieces of information, some hot topics and emerging news will become much more popular in a very short time with the help of this information spreading platform of microblogs. In these "super spreading events", messages are transmitted to a vast range of individuals through a small portion of users...
Big Data presents challenges for predictive analytic algorithms due to the possibility of non-stationary populations. Concept drift detection algorithms can be used to detect changes in underlying distribution in order to retrain. Most concept drift detection methods are known to scale to a relatively low number of features (a few hundred). However, in many areas, datasets with thousands or even tens...
Generative models for graphs are increasingly becoming a popular tool for researchers to generate realistic approximations of graphs. While in the past, focus was on generating graphs which follow general laws, such as the power law for degree distribution, current models have the ability to learn from observed graphs and generate synthetic approximations. The primary emphasis of existing models has...
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