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Big Data Social Network Analysis fuelling Marketing improvement


A social network is a social structure that links actors (individuals and organizations), and highlights how actors are connected, from a simple relationship to family ties. We are all part of many networks that correspond to the dimensions of our life (family, study, work, leisure activities). Our membership, our activities, our place in these networks are for marketers a valuable source of information, knowledge and opportunities for actions to promote their offers, according to the principle that the behavior of individuals is in part related to the structures in which they operate.

The internet has facilitated the development, the life of social networks, and marketers have acquired the appropriate analytical techniques to exploit them. In fact, a network can be represented as a graph and be mathematically analyzed. In these approaches, the actors are nodes and relationships are links, forming a model where all significant relationships can be analyzed via the construction of a matrix to represent the network. We can then obtain a graph using mathematical treatments performed on matrices, and search the presence of a clique, a chain, a cycle that characterizes the network. Finally using algorithm it is possible to calculate the degrees of strength and the density between social entities, for example, determine the social capital of actors.

There are many measures of connections, distances, power, prestige: the number of nodes, number of links present versus the number of links possible, the sum of links to other members, the degree of density, degree of cohesion, betweeness, path length, the degree to which any member of the network can reach other members of the network, structural holes, etc.. Thus we can characterize both a network and each actor, for example, to identify key people who have an important role in communication and influence.

The analysis of social networks is valuable for example for controlling the flow of information, improve / enhance communication, improve the resilience of a network, find community, or to trust a community. For marketers this is an opportunity to better understand, target, approach clients, prospects, suspects, to sell them more, for better lead communities, to innovate, differentiate themselves from the competition and develop a competitive advantage.

Companies, such as Myspace, LinkedIn or Mzinga, have understood the importance of this type of approach and already widely practiced social network analysis, launching new products, improving the experiences of their customers and satisfying them better. Mzinga in particular, whose business is to provide a means for facilitating communities of clients, provides tools for network analysis. Thus the 14,000 communities, with 40 million people who are managed with Mzinga tools, can be analyzed by their leaders and allow them to optimize their operations.

But be careful, for analysing social networks you must use others solutions than traditional analytical approaches based on relational databases and BI tools. The companies mentioned above already practicing this type of analysis, have had to develop by their own their analytical applications. They use particularly new kind Hadoop solutions and / or Teradata Aster and implement MapReduce programs that involve specific facilities and specialists in this type of analysis. To go further on the experiences of the companies mentioned above, you can access useful information about them via the link below:


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