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This work proposes a system for the analysis and the comparison of users profiles in social networks. Posts are extracted and analyzed in order to detect similar contents, like topics, sentiments and writing styles. A case study regarding the analysis of the authenticity of profiles of the Italian prime minister in different social networks is illustrated.
We address the problem of record linkage and semantic integration in the context of large collections of user-generated content. These datasets are often large since it contains the contributions of millions of Internet users. We present an approach based on approximate string matching between the metadata associated with such data. The discovered linkages are stored in an ontology for answering queries...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.