Is the polarity of content producers strongly influenced by the results of the event?

This paper presents an approach to compare two types of data, subjective data (Polarity of Pan American Games 2011 event by country) and objective data (the number of medals won by each participating country), based on the Pearson corre- lation. When dealing with events described by people, knowledge acquisition is difficult because their structure is heterogeneous and subjective. A first step towards knowing the polarity of the information provided by people consists in automatically classifying the posts into clusters according to their polarity. The authors carried out a set of experiments using a corpus that consists of 5600 posts extracted from 168 Internet resources related to a specific event: the 2011 Pan American games. The approach is based on four components: a crawler, a filter, a synthesizer and a polarity analyzer. The PanAmerican approach automatically classifies the polarity of the event into clusters with the following results: 588 positive, 336 neutral, and 76 negative. Our work found out that the polarity of the content produced was strongly influenced by the results of the event with a correlation of .74. Thus, it is possible to conclude that the polarity of content is strongly affected by the results of the event. Finally, the accuracy of the PanAmerican approach is: .87, .90, and .80 according to the precision of the three classes of polarity evaluated.

Is Europe ready to provide a pan-European Identity Management System?

European public administrations must manage citizens' digital identities, particularly considering interoperability among different countries. Owing to the diversity of electronic identity management (eIDM) systems, when users of one such system seek to communicate with governments using a different system, both systems must be linked and understand each other. To achieve this, the European Union is working on an interoperability framework. This article provides an overview of eIDM systems' current state at a pan-European level. It identifies and analyzes issues on which agreement exists, as well as those that aren't yet resolved and are preventing the adoption of a large-scale model.