OERs recommendation for entrepreneurship using a framework based-on Social Networks Analysis
In these days much of the information published on the Web is published on social media, represented through social networks such as Facebook, Twitter, to name only the most prominent. Each of the media and social networks has its own scheme of operation and different working characteristics, for ex...
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| 格式: | article |
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2015
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| 在线阅读: | http://dspace.utpl.edu.ec/handle/123456789/19019 |
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添加标签 | 总结: | In these days much of the information published on the Web is published on social media, represented through social networks such as Facebook, Twitter, to name only the most prominent. Each of the media and social networks has its own scheme of operation and different working characteristics, for example Twitter is a social network where millions of daily messages called Tweets are exchanged, within the message can be used labels, called hashtags, to identify the subject of the message, the message also may include links to other resources that expand the original content or showing interesting information and the relationships between users are represented as non reciprocal relationships named "Following". The extraction of information posted on social networks is solved in this research through the use of linked data, that allow retrieving resources and link with other external sources, graphs that help represent the working scheme of a social network, and with social network analysis (SNA), technique to discover relevant information that goes beyond the individual properties. The scope of this paper is to use information that is published on Twitter to extract and recommend Open Educational Resources, which will be used in StartUP project. The StartUP project (Intelligent training needs assessment and Open Educational Resources to foster Entrepreneurship) is a project co-funded with support by the European Commission under the Lifelong Learning Programme, which has as specific objective provide effective open educational resources corresponding to individual learning needs. The results obtained are a set of recommendations on users (identified as experts), hashtags (thematic related), and URL (digital resources), according to the main competence areas defined by StartUp. This information will form part on learning paths provided by the project platform. |
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