Hi,
My name is Rocío Martínez Torres. I am an Associate Professor in the department of Business and Management at the University of Seville (Spain). I am researching on topics related to the extraction of data from the web and their analysis through the use of Social Network Analysis and Semantic Analysis techniques (e-social sciences) for many years. These topics could be summarized in the next research lines:
1. Virtual communities: This research line is focused on analyzing the patterns of behaviour of virtual/online community users by modelling their interactions as a social network. The topological features of users participation (degree, centrality, clustering coefficient, ...) are extracted using Social Network Analysis techniques, while the content of the interchanged information is analysed using semantic techniques like Latent Semantic Indexing. The aim consist of obtaining the user profiles attending to their participation features, the structure of the community, the ability of the community to attract new users that can become experts, the main topics of discussions within the community and the ability of the community to create and share knowledge.
2. Open Source Software communities: The previous techniques were used in the analysis of open source software communities. They represent a clear example of collective intelligence paradigm. Data are extracted from the information contained in the distribution lists, which are publicly available from the project website. A specific crawler was designed for this task. The features of participation and of shared knowledge are processed through computational intelligence techniques (Genetic Algorithms, Particle Swarm Optimization) to obtain the structure of the communities and the different users’ profiles.
3. Open innovation communities: This is another emerging paradigm in innovation, based on the idea that organizations should also rely on ideas and knowledge developed externally. One of the most popular schemes for open innovation implementation is through open innovation communities, where users can post, share, comment and evaluate ideas using a specific website managed by an organization (i.e. Dell IdeaStorm, My Starbucks Idea,...). Users can interact among them and also with the innovation departments and experts of the organization. Again, shared ideas, interactions among users and the evaluations and scores received by posted ideas can be extracted and processed from the open innovation website. My main words around this topic consisted of identifying lead users within innovation communities as an alternative to collective scoring methods.
4. Website structure analysis through link analysis: the hyperlink structure of websites can be also modelled as a social network, extracting the data through the use of a crawler that explore the complete website looking for links to other internal and external web pages. My work in this research line was focused on analyzing the accessibility and navigability of institutional websites, classifying them according to several base structures. Moreover, we have also developed the concept of local visibility of websites as an alternative to the idea global visibility used by search engines.
5. Knowledge networks: Knowledge networks of Higher Education institutons in the UK were analyzed using the ISI citation index databases. This was a joint work with Prof. Nik Bessis from the University of Derby, UK, as a result of my stay at this University for three months. By analyzing the joint research papers, it is possible to obtain the collaborations among Universities and their internationalization policies.
I think al these research lines are related to the activity of this TF15: Web data collection from non-reactive sources.
I think we could work together in the advance of this TF.
