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Companies today are developing business strategies taking into consideration behavior of their customers through social networks, which have allowed to extract large amounts of relevant data about users. This is why it has been necessary to apply data mining techniques to find patterns that describe the preferences of users in different contexts. This paper describes the results of using data mining...
This paper simulates Companies' ego networks on Twitter, meaning the companies' number and type of followers. Evident from our data, we show that followers' distribution, in our focus, is neither scale free nor random, thus common network simulations cannot be used to mimic observed data. We present novel rate equations model to capture the complex dynamics of these ego networks.
Recent increases in the adoption of Online Social Networks (OSNs) for advertising has resulted in the research and development of algorithms that can maximize the resulting revenue. OSN users are likely to be influenced by their friends; therefore, one can leverage friendship relationships to determine how advertisements should be distributed among users. If a user is given an indication that their...
One highly studied topic in the field of social networks is the search for influential nodes, that when seeded (i.e. infected intentionally), may infect a large portion of the network through a viral process. However, when it comes to the spread of new products, such viral processes are rather rare. Social influence is indeed an important factor when it comes to the act of adopting a new product....
We use mobile phone records for the analysis of mobility patterns and the detection of possible risk zones of Chagas disease in two Latin American countries. We show that geolocalized call records are rich in social and individual information, which can be used to infer whether an individual has lived in an endemic area. We present two case studies, in Argentina and in Mexico, using data provided...
In recent years, along with the prevalence of social networking sites, the illustrators of Wretch have accordingly transferred to new community platform. These illustrator's fan pages have become popular through viral marketing. Many companies have spotted enormous business opportunities and then worked with illustrators to boost sales by combining illustrators and commercial products. By utilizing...
Traditional viral marketing problems aim at selecting a subset of seed users for one single product to maximize its awareness in social networks. However, in real scenarios, multiple products can be promoted in social networks at the same time. At the product level, the relationships among these products can be quite intertwined, e.g., competing, complementary and independent. In this paper, we will...
The paper discusses the bias of investors and the affect it has on the volatility of the stocks in the market. We also show how sentiment analysis can be run on the pulled tweets and why we chose the Microsoft Azure sentiment analyzer over the other commercial sentiment analyzer tools. Finally, we provide some future direction where we plan to take this research forward and conclude with some closing...
The explosion of mobile phone communications in the last years occurs at a moment where data processing power increases exponentially. Thanks to those two changes in a global scale, the road has been opened to use mobile phone communications to generate inferences and characterizations of mobile phone users. In this work, we use the communications network, enriched by a set of users' attributes, to...
The development of Internet and social networks has provided more emerging network data which facilitates the dynamic network analysis. In this paper, we propose a new method to measure coherence strength, also referred to as community consistency, of a community under dynamic settings. In order to better interpret the influence of evolving community structure on community consistency, we model the...
Relational learning in networked data has been shown to be effective in a number of studies. Relational learners, composed of relational classifiers and collective inference methods, enable the inference of nodes in a network given the existence and strength of links to other nodes. These methods have been adapted to predict customer churn in telecommunication companies showing that incorporating...
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