Online discussion forums allow learners to maintain discussions about their learning process at any time and any place; where they can express their concerns and ideas, and organize their thoughts. ...Indeed, online discussion forums are used as an indicator of learner's performance. In this context, this paper presents the Social Learning Analytics (SLA) process to describe the interactions between learners in an online discussion forum in Moodle using the Pajek visualization tool.
Localizando geográficamente las redes personales Ruiz, Alejandro A.; Molina, José Luis; Teves, Laura
Redes : revista hispana para el análisis de redes sociales,
08/2005, Letnik:
8
Journal Article
Recenzirano
Odprti dostop
In the listserv REDES was carried on a personal network survey with the aim of exploring the value of combining both network and geographical data (through the latitude and longitude of each ...nominee). The survey was done with the aid of the Egonet software. The results of the experience show that this combination allows new insights in the data, specially the spatial distribution of social relationships and their associate exchanges.
Localizando geográficamente las redes personales José Luis Molina; Alejandro Ruiz; Laura Teves
Redes : revista hispana para el análisis de redes sociales,
01/2005, Letnik:
8, Številka:
1
Journal Article
Recenzirano
Odprti dostop
Resumen Con el objetivo de explorar las potencialidades de la combinación de datos procedentes de redes sociales e información geográfica, se llevo a cabo una encuesta de redes personales con la ...ayuda del programa Egonet entre miembros del listserv REDES. En esta encuesta se identifica la latitud y la longitud de las personas nominadas. Los resultados de la experiencia demuestran que esta combinación permite explorar un campo de extraordinario interés como es la distribución espacial de los tipos de relaciones sociales y los intercambios asociados. Abstract In the listserv REDES was carried on a personal network survey with the aim of exploring the value of combining both network and geographical data (through the latitude and longitude of each nominee). The survey was done with the aid of the Egonet software. The results of the experience show that this combination allows new insights in the data, specially the spatial distribution of social relationships and their associate exchanges.
Social Network Analysis Tools Akhtar, Nadeem
2014 Fourth International Conference on Communication Systems and Network Technologies,
04/2014
Conference Proceeding
Social networks like Facebook, Twitter, and Google+ are most visited domains on the Internet. They contain huge data about the users and the relationships among them. To analyze and mine useful ...information from these huge social network data, special graph based mining tools are required that can easily model the structure of the social networks. A number of such analysis tools are available with their own features and benefits. Choosing an appropriate tool for a particular task is difficult to decide. This work present a comparative analysis of four social network analysis tools-Network, Gephi, Pajek, IGraph based on platform, execution time, Graph types, algorithms complexity, input file format and graph features.
The purpose of this research is to reveal the process of the growth of a new venture group in terms of the investment in spin-offs and the instability of the group domain. SoftBank Group (SBG), ...consisting of SoftBank Corp and its spin-offs, is chosen for our study. Our database includes data sourced from the securities reports of the spin-offs from SoftBank Corp, and the database is used for analysis using the networking analysis software named “Pajek Version2.05”. The followings are found in our study. (1) Spin-off companies have been created in SBG through the allocation of financial resources for each segment. (2) Group domain of SBG has changed by developing the spin-offs at the early stage, and by Merger and Acquisitions at the later stage. (3) SBG creates spin-off companies not only at each company level but at segment (aggregate of companies) level. he implications of our study are as follows. (1) Our study shows the validity to understand the spin-off phenomenon from the point of view of resource allocations rather than that of entrepreneurs. (2) It is suggested that we should observe both spin-offs and the 'maternal' organization to study the change of the group domain. (3) It's implied that another organization model, called Type-F (Fund), might be required. SoftBank Corp plays a role similar to an investment fund in our study. However, there are three limitations of this paper. (1) The analysis is conducted only from the point of financial resources, not that of human resources. (2) The survey didn’t analyze the change of each spin-off. (3) Causal relationships between the development of spin-offs in/as the group and the change of group domain weren't made clear in our study. In order to challenge these limitations, the quantitative analysis for each spin-offs are required to improve the robustness of our study.
With the growth and large-scale usage of social networks in the dissemination of knowledge in Higher education Institutions, a need is being increasingly felt to tame and utilize this vast (read Big) ...data for a more worldly use. With the use of various NASA (Network Analysis Software Applications) Tools, this aim can be easily achieved. NASA can be applied to various online social media networks generated data sets used by Educational Institutions like Twitter, Linked, or Proprietary Institution specific platforms for predicting and formulating student specific academic, safe-campus, and business strategies. As widely known, the above-listed social media (SM) applications help us in sharing digital artifacts (antiques) and capturing digital footprints. The common utility among these social media applications is that they are able to create natural network data. These OSMNs (online social media networks) represent the links or relationships between content generators as they look, react, comment, or link to one another’s content. There are many forms of computer-mediated social interaction which includes SMS messages, emails, discussion groups, blogs, wikis, videos, and photo sharing systems, chat rooms, and “social network services”. All these applications generate social media datasets of social friendships. Thus OSMNs have academic and pragmatic value and can be leveraged to illustrate the crucial contributors and the content. Our study takes all the above into account and thus shall explore the various Network Analysis Software Applications to study the practical aspects of big data analytics that can be used to better strategies Higher learning Institutions.
pajek2stata imports data stored in Pajek's ".net" format for relational data (social networks). The part of the data containing information on the vertices is stored in Stata variables, while the ...part containing information on relations is stored as a Mata matrix.
Anthropology White, Douglas R.; Batagelj, Vladimir; Mrvar, Andrej
Social science computer review,
10/1999, Letnik:
17, Številka:
3
Journal Article
Recenzirano
Five key problems of kinship networks are boundedness, cohesion, size and cohesive relinking, types of relations and relinking, and groups or roles. Approaches to solving these problems include ...formats available for electronic storage of genealogical data and representations of genealogies using graphs. P-graphs represent couples and uncoupled children as vertices, whereas parent-child links are the arcs connecting nodes both within and between different nuclear families. Using results from graph theory, P-graphs are shown to lend themselves to solutions of the problems discussed. Relinking of families through marriage, for example, can be formally defined as sets of bounded groups that are the cohesive cores of kinship networks, with nodes at various distances from such cores. The structure of such cores yields an analytic decomposition of kinship networks and constituent group and role relationships. The Pgraph and Pajek programs for large network analysis help both to represent kinship networks and their patterns and to solve problems of analysis.
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