Exploring the Properties of Online Social Network Data and Their Implications for Consumer Social Data Analytics

Exploring the Properties of Online Social Network Data and Their Implications for Consumer Social Data Analytics

Yamen Koubaa (France Business School, France)
Copyright: © 2014 |Pages: 21
DOI: 10.4018/978-1-4666-5194-4.ch009

Abstract

The prediction of consumer behavior is largely based on the analysis of consumer data using statistics as a tool for prediction. Thanks to online social networks, large quantities of heterogeneous consumer data are now available at competitive costs. Though they have much in common with conventional data, online social network datasets display several different properties. The exploration of these unique properties is indispensable to insuring the accuracy of predictions and data analytics. This chapter presents online social data, discusses seven properties of online social network data, suggests some analysis tools, and draws implications regarding the use of social data analytics.
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Online Social Networks

Nature has made it essential for humans to interact and exchange, to create social networks of some form. Especially in the business community, networking is often vital for the success of firms. Network ties allow for the exchanging of ideas, problem solving, opportunities sharing, and allows for access to knowledge while saving time and energy. Networks have been always effective in satisfying the informational needs of businesses; whether the objective is to learn about a customer or a competitor, to get information about new offers, to get updated about a new legislation or policy, or to catch new opportunities The effectiveness of social networks is due mainly to a structure that allows the instant exchange of data across multiple and often distant actors.

A network is made of nodes and relationships. The nodes are the participants or actors inside the network. The actors create, transform, receive and send information. One actor is at the same time a stimulator and a reactor. He stimulates other actors by issuing signals (e.g., comments on a post) and reacts to others’ stimulations. The relationships are the links between the actors. They are the channels through which the stimuli and the reactions created by the actors are transferred. These interactions allow for immediate access to information sources, a cross-fertilization of ideas and an identification of key influencers within the network, all of which lead to knowledge creation and optimization.

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