30 May 2013
The mobile apps industry has a huge potential and is experiencing strong growth rates. The use of this kind of apps is largely linked to that of social networks, but, in this era of explosive growth in the volume of information and the variety of resources, filtering the knowledge available is becoming increasingly challenging for the end user. The innovative SOCAM project aims at developing an open-source operating system for mobile devices. This OS will include a module for the analysis of social networks, aimed at feeding app recommendation engines. This tool will enable users to identify the apps that are best suited to their needs or preferences.
SOCAM’s Social Network Analysis (SNA) module attempts to overcome the difficulties users are finding to navigate, search and classify the contents available in the mobile apps markets, by helping them filter the overwhelming variety of choices available, to spot on those most relevant to them. The system learns what the user needs, and knows when and how to present it.
The SOCAM system will also allow app developers to retrieve special-purpose feedback, enabling them to improve their product and the end user experience. In addition, it will help the best apps to quickly propagate across the community of users of the Operating System, which can be very appealing for app developers, that nowadays need to make substantial investments in marketing, or rely on luck, to ensure that their apps will have enough visibility and reach a success level in line with their quality.
The SOCAM research project, that has been under way since October 2011, is led by the privately-owned companies Zed Worldwide S.A. and Factory Holding Company 25 S.L. (FHC25). The SNA module is being developed in cooperation with the Madrid Research Institute IMDEA Networks, with the support from the Rey Juan Carlos and Carlos III Universities of Madrid.
Analyzing social networks from the network science perspective provides a rich, extensive, context-related, geographically focused and virtually immediate information that enables to go far beyond traditional marketing studies. It can be very useful to understand and predict the users’ behaviors, and to develop and recommend apps tailored to their needs. Due to the huge scale of the networks to be analyzed in this project, it will be necessary to bring forward the state of the art in the field of tools and technologies for Big Data (the area that studies the processing of enormous volumes of data), to apply them in the analysis of networks.
Social networks have nowadays become major subjects of research and analysis in multiple disciplines. The Social Networks Analysis (SNA) concept this project is based on focuses on the analysis of each member or group belonging to the network as a node that generates shared knowledge and human relations. The complex structure of the networks is analyzed by using concepts such as centrality, degree of relation, or distance across the network between the players (individuals or groups) making them up. This approach enables to identify leaders, who are those with the highest number of contacts and activity and, therefore, the strongest influence. The information raised from this analysis provides an unprecedented view about the decision-making and behavioral mechanisms associated to the consumption patterns, a highly valuable information to focus market research, marketing efforts and sales activity on the targeted and effective sale of products, such as the mobile apps, to specific individuals and groups. In other words, the aim is bringing knowledge to those who could potentially be interested in using it, and only to them. Moreover, the intention is to bring that information to the most influential and opinion-leading nodes in the network, so that they may become a path to spread this knowledge across their inner circle, for instance as a comment or an explicit recommendation.