Social Academic Networks (research)

In the Web 2.0 perspective not only the technological and content aspects but also the social interactions and its relational aspects must be considered. In this scenario, emerged applications with social aspects including Web-based communities and Social Networks. In a first work [1] we developed a framework to evaluate the users’ qualification and reputation in an environment of open authorship and revision. Following this direction we analyzed the quality of Program Committees and Editorial Boards by statistics methods [2]. Immediately after we realized that a deeper analysis of co-authorship may produce good quality indicators and we started the analysis of Academic Social Network.

The Social Network Analysis (SNA) is based on the assumption that the relationship’s importance between interaction elements is a central point for analysis. The increasing interest in SNA research is encouraged by the popularization of online social networks. Our example of SNA concepts application is to model an Academic Social Network representing collaboration among researchers by the use of co-author relationships. Following, we present an overview of our research focusing on Academic Social Networks including models for analysis, dissemination and recommendation in this context. In a first paper [3] we introduced a set of challenges for developing a dissemination service over a Web collaborative network. Specific metrics were defined for working on a co-authorship network. As a case study, we build such a network using those metrics and compare it to a manually built one. Specifically, once we build a collaborative network and verify its quality, the overall effectiveness of the dissemination services will also be improved. A dissemination service is established by data producers and consumers. Specifically, consumers subscribe to the service by defining a pro file, which is usually composed of different queries. As the producers introduce new data, usually through messages, the dissemination service evaluates each message against the profiles. Once there is a match between a profile and a message, the service sends that message to the correct profile’s consumer. The results are evaluated by the access patterns and users accordance with the quality of disseminated papers and, more important, by the increase in the cooperation pattern among inter-institutional researchers.

In a following paper [4] we presented a Collaboration Recommendation on Academic Social Networks. In the academic context, scientific research works are often performed through collaboration and cooperation between researchers and research groups. Researchers work in various subjects and in several research areas. Identifying new partners to execute joint research and analyzing the level of cooperation of the current partners can be very complex tasks. Recommendation of new collaborations may be a valuable tool for reinforcing and discovering such partners. In this work, we have presented the details of an innovative approach to recommend scientific collaborations on the context of Social Networks. From the recommendation analysis it become clear that an analysis of the bibliographic production distribution among the researchers of a group. Finally we developed an analysis including a new relationship weighted approach. These weights aim to measure the importance of the relational ties between actors and are important to be considered in an Academic Social Network. In our case study, we demonstrated the possibility of uses of the Gini coefficient to analyze weighted Social Networks [5]. Gini coefficient is applied to measure the homogeneity level of the collaboration, i.e., if only a few researchers keep a good level of collaboration or if all researchers of the network, indeed, are contributing for the group. Some of the metrics more commonly used for Social Networks Analysis (SNA) do not consider the weights of relationships between the actors of the analyzed Social Network, if it exists. These weights aim to measure the importance of the relational ties between actors and also are important to be considered in a SNA. Our initial results demonstrate the validity and applicability of this approach for a collaboration of Brazilian network scientists.

We introduced the architecture for recommending collaborations [7], [8]. A case study to validate the approach, using researchers associated to the InWeb project, was also presented.

The developed researches demonstrate the importance of applying the concepts of Social Networks to the analysis and quality improvement of academic groups. Additionally, we proposed new measures to adequately quantify the groups’ quality for generating ranks [9], [10].


References

[10] Roberto da Silva, Fahad Kalil, Alexandre Souto Martinez and José Palazzo Moreira de Oliveira,Universality in Bibliometrics, Physica. A (Print), v. 1, p. j.physa.2011.11, 2012.

[9] Giseli Rabello Lopes, Mirella M. Moro, Roberto da Silva; Eduardo Martins Barbosa, José Palazzo Moreira de Oliveira. Ranking Strategy for Graduate Programs Evaluation. In: The 7th International Conference on Information Technology and Application (ICITA 2011), 2011, Sydney, Australia. Proceedings of The 7th International Conference on Information Technology and Application (ICITA 2011), 2011.

[8] Eduardo Martins Barbosa, MORO, Mirella M. Moro, Giseli Rabello Lopes, José Palazzo Moreira de Oliveira. VRRC: Uma Ferramenta Web para Visualização e Recomendação em Redes de Coautoria. In: VIII Sessão de Demos, Simpósio Brasileiro de Banco de Dados (SBBD 2011), Florianópolis. Anais do Simpósio Brasileiro de Banco de Dados, 2011.

[7] Giseli Rabello Lopes, Mirella Moura Moro,José Palazzo Moreira de Oliveira: Temporal Influence in Collaborators Recommendation on Social Networks, IADIS WWW-Internet 2011,Session FP 7.1.

[6] José Palazzo Moreira de Oliveira, Giseli Rabello Lopes, Mirella Moura Moro: Academic Social Networks. ER Workshops 2011: 2-3

[5] Giseli Rabello Lopes, Roberto da Silva, José Palazzo Moreira de Oliveira: Applying Gini coefficient to quantify scientific collaboration in researchers network. WIMS 2011: 68

[4] Giseli Rabello Lopes, Mirella M. Moro, Leandro Krug Wives, José Palazzo Moreira de Oliveira: Collaboration Recommendation on Academic Social Networks. ER Workshops 2010: 190-199

[3] Giseli Rabello Lopes, Mirella M. Moro, Leandro Krug Wives, José Palazzo Moreira de Oliveira: Cooperative Authorship Social Network. AMW 2010

[2] Roberto da Silva, José Palazzo Moreira de Oliveira, José Valdeni de Lima, Viviane Moreira: Statistics for Ranking Program Committees and Editorial Boards CoRR abs/1002.1060: (2010)

[1] Gabriel Simões, Leandro Krug Wives, José Palazzo Moreira de Oliveira: Open Publication System: Evaluating Users Qualification and Reputation. CSEDU 2009: 200-205